Monitor-Centric Interpretation of Offset Pressure Monitoring Measurements

Abstract

A method for monitor-centric interpretation of offset pressure monitoring measurements includes simultaneously hydraulic fracturing treatment stages corresponding to treatment wells, measuring corresponding pressure data via pressure gauge(s) at monitor well(s), detecting pressure responses corresponding to fracture hits within the pressure data, and determining a reasonable velocity window for when a fracture originating from each treatment stage is likely to affect the pressure data. The method includes detecting treatment stage(s) that are likely to be the origin of each fracture hit based on the reasonable velocity window and, for each fracture hit that only has one likely originating treatment stage, assigning the detected fracture hit to such treatment stage. The method includes determining observation property data corresponding to the treatment stages that have been assigned to the fracture hits and iteratively assigning, based on such data, each unassigned fracture hit to one of the corresponding likely originating treatment stages.

Description

CROSS-REFERENCE TO RELATED APPLICATION

This application claims priority to and the benefit of U.S. Provisional Application No. 63/583,921, entitled “Monitor-Centric Interpretation of Offset Pressure Monitoring Measurements,” having a filing date of Sep. 20, 2024, the disclosure of which is incorporated herein by reference in its entirety.

FIELD OF THE INVENTION

The techniques described herein relate generally to the field of hydrocarbon well completions and hydraulic fracturing operations. More specifically, the techniques described herein relate to monitor-centric interpretation of offset pressure monitoring measurements.

BACKGROUND OF THE INVENTION

This section is intended to introduce various aspects of the art, which may be associated with embodiments of the present techniques. This discussion is believed to assist in providing a framework to facilitate a better understanding of particular aspects of the present techniques. Accordingly, it should be understood that this section should be read in this light, and not necessarily as admissions of prior art.

Low-permeability hydrocarbon reservoirs are often stimulated using hydraulic fracturing techniques. Hydraulic fracturing consists of injecting a volume of fracturing fluid through created perforations and into the surrounding reservoir at such high pressures and rates that the reservoir rock in proximity to the perforations cracks open and extends outwardly in proportion to the injected fluid volume. This results in the creation of hydraulic fractures that serve as a conduit for fluid within the reservoir, thus permitting hydrocarbon fluids to flow into the wellbore and then be produced at the surface.

In operation, the success of the hydraulic fracturing process has a direct impact on the production characteristics of the corresponding hydrocarbon well. Therefore, it is desirable to collect information regarding the location, propagation, and resulting three-dimensional geometry of the created hydraulic fractures. Such information is often collected using a treatment well and monitor well pair. In such cases, because only a single treatment well is being hydraulically fractured within the vicinity of the monitor well, there is very little uncertainty regarding the origin of the pressure response that is observed at the monitor well, and the offset pressure analysis is typically performed from the perspective of the treatment well. However, in many cases, it is desirable to collect offset pressure measurements from one or more monitor wells while multiple treatments wells are being hydraulically fractured simultaneously (or during time intervals that at least partially overlap) across multiple pads. In particular, collecting offset pressure measurements in such scenarios would enable the fracture geometry to be accurately characterized in multiple directions rather than only a single direction. However, in such cases, because the pressure data correspond to multiple treatment wells that were hydraulically fractured at overlapping time intervals, it is difficult to accurately identify which treatment well is responsible for each fracture hit observed in the pressure data. As a result, accurate fracture characterization is challenging in such scenarios.

SUMMARY OF THE INVENTION

An embodiment described herein provides a method for monitor-centric interpretation of offset pressure monitoring measurements. The method includes simultaneously hydraulic fracturing treatment stages corresponding to multiple treatment wells within the vicinity of one or more monitor wells and measuring, via one or more pressure gauges positioned at the monitor well(s), pressure data during the hydraulic fracturing of the treatment stages. The method includes detecting, via a computing system, pressure responses corresponding to fracture hits within the pressure data, as well as determining a reasonable velocity window for when a hydraulic fracture originating from each treatment stage is likely to affect the pressure data measured at the monitor well(s). The method also includes identifying one or more treatment stages that are likely to be the origin of each detected fracture hit based on the reasonable velocity window and, for each fracture hit that only has one treatment stage that is likely to be the origin, assigning the detected fracture hit to the treatment stage. The method further includes determining observation property data corresponding to at least a portion of the treatment stages that have been assigned to the fracture hits and iteratively assigning, based on the observation property data, each remaining, unassigned detected fracture hit to one of the corresponding treatment stages that is likely to be the origin and has not yet been assigned to one of the fracture hits.

Another embodiment described herein provides a hydrocarbon well system. The hydrocarbon well system includes multiple treatment wells and one or more monitor wells including one or more pressure gauges that measure pressure data during the simultaneous hydraulic fracturing of treatment stages corresponding to the treatment wells. The hydrocarbon well system also includes a computing system that is communicably coupled to the monitor well. The computing system includes a processor and a non-transitory, computer-readable storage medium including program instructions that are executable by the processor to cause the processor to execute the method described above (or any suitable variation thereof).

Another embodiment described herein provides a non-transitory, computer-readable storage medium. The non-transitory, computer-readable storage medium includes program instructions that are executable by a processor to cause the processor to execute the method described above (or any suitable variation thereof).

Another embodiment described herein provides a method for monitor-centric interpretation of offset monitoring measurements. The method includes simultaneously hydraulic fracturing treatment stages corresponding to multiple treatment wells within the vicinity of one or more monitor wells and measuring, via monitoring equipment positioned at the monitor well(s), offset monitoring data during the hydraulic fracturing of the treatment stages. The method includes detecting, via a computing system, monitoring responses corresponding to fracture hits within the offset monitoring data, as well as determining a reasonable velocity window for when a hydraulic fracture originating from each treatment stage is likely to affect the offset monitoring data measured at the monitor well(s). The method also includes identifying one or more treatment stages that are likely to be the origin of each detected fracture hit based on the reasonable velocity window and, for each fracture hit that only has one treatment stage that is likely to be the origin, assigning the detected fracture hit to the treatment stage. The method further includes determining observation property data corresponding to at least a portion of the treatment stages that have been assigned to the fracture hits and iteratively assigning, based on the observation property data, each remaining, unassigned detected fracture hit to one of the corresponding treatment stages that is likely to be the origin and has not yet been assigned to one of the fracture hits.

These and other features and attributes of the disclosed embodiments of the present techniques and their advantageous applications and/or uses will be apparent from the detailed description that follows.

BRIEF DESCRIPTION OF THE DRAWINGS

To assist those of ordinary skill in the relevant art in making and using the subject matter described herein, reference is made to the appended drawings, where:

FIG. 1 is a simplified schematic view of a multi-pad configuration in which treatment stages corresponding to treatment wells from three pads are stimulated simultaneously, resulting in monitor wells measuring pressures responses originating from multiple treatment stages over overlapping completion times;

FIG. 2 is a simplified process flow diagram of an exemplary process for interpreting pressure data measured via one or more monitor wells in accordance with the present techniques;

FIG. 3 is a graph of a smoothed pressure curve representing offset pressure data measured at a monitor well during the hydraulic fracturing of multiple treatment stages in the vicinity of the monitor well;

FIG. 4 includes a first graph showing measured pressure data from a monitor well (along with the detected fracture hits), as well as a second graph depicting likely originating treatment stages for each fracture hit in the first graph;

FIG. 5 includes a collection of graphs of several types of observation property data from two treatment wells including stages that have already been assigned to specific fracture hits;

FIGS. 6A and 6B include a collection of graphs that represent a complex exemplary implementation of the present techniques for multiple treatment wells that are simultaneously fractured;

FIG. 7 is a process flow diagram of an exemplary method for monitor-centric interpretation of offset pressure monitoring measurements in accordance with the present techniques;

FIG. 8 is a block diagram of an exemplary cluster computing system that may be utilized to implement at least a portion of the present techniques; and

FIG. 9 is a block diagram of an exemplary non-transitory, computer-readable storage medium that may be used for the storage of data and modules of program instructions for implementing at least a portion of the present techniques.

It should be noted that the figures are merely examples of the present techniques and are not intended to impose limitations on the scope of the present techniques. Further, the figures are generally not drawn to scale, but are drafted for purposes of convenience and clarity in illustrating various aspects of the techniques.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

In the following detailed description section, the specific examples of the present techniques are described in connection with preferred embodiments. However, to the extent that the following description is specific to a particular embodiment or a particular use of the present techniques, this is intended to be for exemplary purposes only and simply provides a description of the embodiments. Accordingly, the techniques are not limited to the specific embodiments described below, but rather, include all alternatives, modifications, and equivalents falling within the true spirit and scope of the appended claims.

At the outset, and for ease of reference, certain terms used in this application and their meanings as used in this context are set forth. To the extent a term used herein is not defined below, it should be given the broadest definition those skilled in the art have given that term as reflected in at least one printed publication or issued patent. Further, the present techniques are not limited by the usage of the terms shown below, as all equivalents, synonyms, new developments, and terms or techniques that serve the same or a similar purpose are considered to be within the scope of the present claims.

As used herein, the singular forms “a,” “an,” and “the” mean one or more when applied to any embodiment described herein. The use of “a,” “an,” and/or “the” does not limit the meaning to a single feature unless such a limit is specifically stated.

The term “and/or” placed between a first entity and a second entity means one of (1) the first entity, (2) the second entity, and (3) the first entity and the second entity. Multiple entities listed with “and/or” should be construed in the same manner, i.e., “one or more” of the entities so conjoined. Other entities may optionally be present other than the entities specifically identified by the “and/or” clause, whether related or unrelated to those entities specifically identified. Thus, as a non-limiting example, a reference to “A and/or B,” when used in conjunction with open-ended language such as “including,” may refer, in one embodiment, to A only (optionally including entities other than B); in another embodiment, to B only (optionally including entities other than A); in yet another embodiment, to both A and B (optionally including other entities). These entities may refer to elements, actions, structures, steps, operations, values, and the like.

As used herein, the term “any” means one, some, or all of a specified entity or group of entities, indiscriminately of the quantity.

The phrase “at least one,” when used in reference to a list of one or more entities (or elements), should be understood to mean at least one entity selected from any one or more of the entities in the list of entities, but not necessarily including at least one of each and every entity specifically listed within the list of entities, and not excluding any combinations of entities in the list of entities. This definition also allows that entities may optionally be present other than the entities specifically identified within the list of entities to which the phrase “at least one” refers, whether related or unrelated to those entities specifically identified. Thus, as a non-limiting example, “at least one of A and B” (or, equivalently, “at least one of A or B,” or, equivalently, “at least one of A and/or B”) may refer, in one embodiment, to at least one, optionally including more than one, A, with no B present (and optionally including entities other than B); in another embodiment, to at least one, optionally including more than one, B, with no A present (and optionally including entities other than A); in yet another embodiment, to at least one, optionally including more than one, A, and at least one, optionally including more than one, B (and optionally including other entities). In other words, the phrases “at least one,” “one or more,” and “and/or” are open-ended expressions that are both conjunctive and disjunctive in operation. For example, each of the expressions “at least one of A, B, and C,” “at least one of A, B, or C,” “one or more of A, B, and C,” “one or more of A, B, or C,” and “A, B, and/or C” may mean A alone, B alone, C alone, A and B together, A and C together, B and C together, A, B, and C together, and optionally any of the above in combination with at least one other entity.

As used herein, the phrase “based on” does not mean “based only on,” unless expressly specified otherwise. In other words, the phrase “based on” means “based only on,” “based at least on,” and/or “based at least in part on.”

As used herein, the term “bench” refers to a target interval or section of a subsurface area that typically shares a substantial number of geologic properties, somewhat analogous to a geological formation.

As used herein, the term “during,” when used in reference to the measurement of pressure data via a monitor well at the time of hydraulic fracturing of multiple treatment wells, is intended to mean (not only concurrently with such hydraulic fracturing) but also immediately after such hydraulic fracturing (where the amount of time encompassed by the term “immediately” may be dictated, at least in part, by reasonable velocity window(s) during which pressure response(s) are expected to be observed at the monitor well).

As used herein, the terms “example,” exemplary,” and “embodiment,” when used with reference to one or more components, features, structures, or methods according to the present techniques, are intended to convey that the described component, feature, structure, or method is an illustrative, non-exclusive example of components, features, structures, or methods according to the present techniques. Thus, the described component, feature, structure, or method is not intended to be limiting, required, or exclusive/exhaustive; and other components, features, structures, or methods, including structurally and/or functionally similar and/or equivalent components, features, structures, or methods, are also within the scope of the present techniques.

As used herein, the term “field” (sometimes referred to as an “oil and gas field” or a “hydrocarbon field”) refers to an area including one or more hydrocarbon wells for which hydrocarbon production operations are to be performed to provide for the extraction of hydrocarbon fluids from a corresponding subterranean formation.

The term “fracture” (or “hydraulic fracture”) refers to a crack or surface of breakage induced by an applied pressure or stress within a subterranean formation. Moreover, as described above, the term “wetted fracture” (or “wetted region” or “wetted hydraulic fracture”) refers to an entire hydraulic fracture, while the term “propped fracture” (or “propped region” or “propped hydraulic fracture”) refers to the region of the hydraulic fracture where proppant is present in enough quantity to prevent the closure of the hydraulic fracture. Furthermore, because the propped region of a fracture is the primary region of the fracture that contributes to the production of hydrocarbon fluids, in some cases, such region may also be referred to as the “productive region” and/or the “conductive region” of the fracture. Relatedly, the term “busted region” is used herein to refer to the non-propped region of the fracture that closes once the hydraulic pressure is released (i.e., the wetted region minus the propped region).

As used herein, the term “fracture hit” refers to the point at which an interaction occurs between two wells. For example, in the case of a monitor well being utilized to measure offset pressure data with respect to multiple treatment stages, the fracture hit for each treatment stage would be the point (e.g., the time) at which a hydraulic fracture originating from the treatment stage interacts with the monitor well, as detected via the pressure data measured at the monitor well.

The term “hydraulic fracturing” refers to a process for creating fractures (also referred to as “hydraulic fractures”) that extend from a wellbore into a reservoir, so as to stimulate the flow of hydrocarbon fluids from the reservoir into the wellbore. A fracturing fluid is generally injected into the reservoir with sufficient pressure to create and extend multiple fractures within the reservoir, and a proppant material is used to “prop” or hold open the fractures after the hydraulic pressure used to generate the fractures has been released.

As used herein, the term “monitor well” refers to any type of well that is utilized to measure offset pressure data corresponding to multiple treatment wells according to embodiments described herein. For example, such monitor well may include a slant well that is configured to measure pressure data from one or more treatment wells within the vicinity of the monitor well. Moreover, the terms “monitor well” and “treatment well” generally refer to the status of a well at a given point in time, not a perpetual state. For example, a well may undergo a hydraulic fracturing operation and will be qualified as a treatment well during this period of time. Afterwards, this same well may become a monitor well used to measure offset pressure data for other nearby hydraulic fracturing operations.

As used herein, the term “simultaneously,” when used in reference to the hydraulic fracturing of multiple treatment stages, is not intended to mean that the treatment stages must be treated during the exact same time interval but, rather, that the treatment stages (or at least some combinations of such treatment stages) are treated during time intervals that at least partially overlap in terms of the reasonable velocity windows for when pressure responses corresponding to the resulting hydraulic fractures are likely to be observed at a monitor well.

The terms “substantial,” “substantially,” “approximate,” and “approximately,” when used in reference to a quantity or amount of a material, or a specific characteristic thereof, refers to an amount that is sufficient to provide an effect that the material or characteristic was intended to provide. The exact degree of deviation allowable may depend, in some cases, on the specific context.

As used herein, the term “surface” refers to the uppermost land surface of a land well, or the mud line of an offshore well, while the term “subsurface” (or “subterranean”) generally refers to a geologic strata occurring below the earth's surface. Moreover, as used herein, “surface” and “subsurface” are relative terms. The fact that a particular piece of equipment is described as being on the surface does not necessarily mean it must be physically above the surface of the earth but, rather, describes only the relative placement of the surface and subsurface pieces of equipment. In that sense, the term “surface” may generally refer to any equipment that is located above the casing strings and other equipment that is located inside the wellbore. Moreover, according to embodiments described herein, the terms “downhole” and “subsurface” are sometimes used interchangeably, although the term “downhole” is generally used to refer specifically to the inside of the wellbore.

As used herein, the term “treatment stage” refers to a stage of a treatment well. Thus, the plural “treatment stages” refers to multiple such stages, where any number of such stages may correspond to the same treatment well or a different treatment well.

The term “wellbore” refers to a borehole drilled into a subterranean formation. The borehole may include vertical, deviated, highly deviated, and/or horizontal sections. The term “wellbore” also includes the downhole equipment associated with the borehole, such as the casing strings, production tubing, gas lift valves, and other subsurface equipment. Relatedly, the term “hydrocarbon well” (or simply “well”) includes the wellbore in addition to the wellhead and other associated surface equipment.

The term “hydrocarbon well system” is used herein to refer to all the hydrocarbon wells and associated equipment within a particular field of interest. More specifically, according to embodiments described herein, a hydrocarbon well system includes at least one treatment well (with the corresponding wellhead, wellbore, and associated downhole and surface equipment) and at least one monitor well (with the corresponding wellhead, wellbore, and associated downhole and surface equipment). In addition, according to embodiments described herein, the hydrocarbon well system includes at least one computing system that enables the direction and execution of various hydrocarbon development tasks with respect to any of the wells within the field, including, for example, completion, stimulation, and production-related tasks.

Turning now to details of the present techniques, as described above, accurate fracture characterization is challenging for scenarios in which one or more monitor wells are used to measure offset pressure data corresponding to multiple treatment wells that are hydraulically fractured at overlapping time intervals. This is illustrated by FIG. 1, which is a simplified schematic view of a multi-pad configuration 100 in which treatment stages 102A, 102B, 102C, 104A, 104B, 106A, 106B, and 106C corresponding to treatment wells from three pads 108, 110, and 112, respectively, are stimulated simultaneously, resulting in monitor wells 114 and 116 measuring pressures responses originating from multiple treatment stages over overlapping completion times (as indicated by the arrows in FIG. 1). In FIG. 1, the arrows with continuous lines indicate a more likely origin of the pressure response observed at the respective monitor well, while the arrows with dashed lines indicate a less likely origin of the pressure response. However, because the wells are stimulated at overlapping time intervals, accurate interpretation of the pressure data is difficult.

Accordingly, the present techniques alleviate this difficulty and provide related advantages as well. In particular, the techniques described herein provide for the monitor-centric interpretation of offset pressure data corresponding to simultaneous hydraulic fracturing operations for stages of multiple treatment wells (i.e., multiple treatment stages). In this context, the term “monitor-centric” refers to the utilization of pressure data measured at the monitor well(s), initially without regard for treatment data measured at the individual treatment wells. According to embodiments described herein, pressure data are measured at the monitor well(s) during the simultaneous hydraulic fracturing of multiple treatment stages. Fracture hits are detected within the pressure data, and each fracture hit is then assigned to the originating treatment stage (i.e., the originating treatment stage for hydraulic fracture(s) that are most likely to be responsible for the particular pressure response corresponding to the fracture hit). This is accomplished by executing a data-driven process of elimination using the measured pressure data (including the detected fracture hits and their properties), data relating to a reasonable velocity window (RVW) for fracture propagation in the subsurface (where such RVW is equal to a range of velocities at which a hydraulic fracture is reasonably expected to grow in the subsurface depending on the distance traveled by said fracture, with such velocity range being informed by prior offset pressure monitoring experiments), and observation property data. As used herein, the term “observation property data” is used herein to refer to both property data corresponding to the treatment stages and property data corresponding to the detected fracture hits relative to the likely originating treatment stages. Moreover, in some embodiments, at least a portion of the observation property data are computed based on the treatment rates and/or pressures of the treatment well.

The present techniques provide various advantages over conventional offset monitoring hydraulic fracturing techniques. As an example, the present techniques provide a monitor-centric approach (i.e., an approach that is primarily based on the offset pressure data recorded at the monitor well, rather than the data collected at the treatment wells), thus enabling the simultaneous collection of pressure responses corresponding to fracture hits from multiple nearby treatment wells. While conventional techniques generally only enable the accurate characterization of hydraulic fractures originating from a single treatment well, the present techniques enable the accurate characterization of hydraulic fractures originating from multiple treatment wells that are hydraulically fractured at overlapping time intervals, therefore allowing interpretations of hydraulic fracture growth in the subsurface that more closely resemble real-time operations, such as hydraulic fracturing operations involving more than one frac crew, and/or zipper fracturing and/or simul-frac. This allows the present techniques to be advantageously applied to complex hydraulic fracturing operations including multiple pads and multiple corresponding fracturing crews operating within proximity to each other. As another example, the present techniques can be performed using any suitable type of monitor well, as long as the desired offset pressure data can be collected from such monitor well. As a result, the present techniques can be easily performed using existing wells without disruptions to normal hydraulic fracturing operations, as is often required for offset pressure monitoring data collection. As another example, the present techniques provide a data-driven, unbiased interpretation process for complex monitoring scenarios. This effectively expands the interpretation of offset pressure monitoring measurements to complex, multi-well scenarios, providing valuable information for performing three-dimensional fracture characterization. Moreover, such fracture characterization can be used to, for example, optimize current hydraulic fracturing operations, to plan future hydraulic fracturing operations, and/or to inform well spacing and stacking plans in the vicinity of the monitor well. Furthermore, a data-driven monitor-centric technique can identify more than a single fracture hit to a single originating treatment stage with a high degree of confidence, thus providing an understanding of the number of hydraulic fractures that grow to the monitor well(s) from a single stage, leading to learnings on completion efficiency directly from offset pressure measurements.

Turning now to more specific details of the present techniques, FIG. 2 is a simplified process flow diagram of an exemplary process 200 for interpreting pressure data measured via one or more monitor wells in accordance with the present techniques. The process 200 may be executed, at least in part, by one or more computing systems including one or more processors, such as the exemplary cluster computing system described with respect to FIG. 8 (or any suitable variation(s) thereof). In some embodiments, such computing system(s) are positioned at the hydrocarbon field at which the relevant wells are located and form part of the overall hydrocarbon well system. For example, the computing system(s) may form part of a mobile command center for directing the operations performed with respect to such wells.

Prior to execution of the process 200 (or as part of the process 200, depending on the details of the particular implementation), hydraulic fracturing is performed for multiple treatment stages simultaneously, and pressure data are measured at one or more monitor wells during such hydraulic fracturing. The resulting pressure data are then input to the process 200 at block 202. At block 204, data preparation is performed. In various embodiments, this includes (but is not limited to) smoothing the pressure data. This is illustrated by FIG. 3, which is a graph 300 of a smoothed pressure curve 302 representing offset pressure data measured at the monitor well(s) during the hydraulic fracturing of multiple treatment stages in the vicinity of the monitor well. Moreover, the graph 300 of FIG. 3 also depicts the observed pressure responses (i.e., fracture hits) as vertical dashed lines, where such pressure responses have not yet been assigned to originating treatment stages.

At block 206, fracture hit detection is performed based on the prepared pressure data. In various embodiments, this includes computing the first and second derivatives of the pressure data from block 204. In various embodiments, the fracture hits are then detected based on the second derivative peaks, and fracture hit timestamps are then refined using a knee/elbow detection workflow which, within the smaller time window around a second derivative peak, can be used to identify the maximum curvature at which the pressure data exhibits the largest slope change, i.e., the exact arrival time of the fracture hit, for example. Refining the timestamp of fracture hits is useful, for example, when the offset pressure monitoring is noisy and/or the pressure increase resulting from the hydraulic fracture is smooth. Moreover, with the monitor-centric approach, the pressure increase between two subsequent hits can be calculated so the amount of pressure increase following a fracture hit is known. False positives resulting from pressure data quality issues can thus be eliminated based on first and second derivatives, and, for example, other relevant criteria, such as the amount of pressure increase observed following the fracture hit.

Once the fracture hits have been detected, the process 200 proceeds to block 208, at which each fracture hit is assigned to a treatment stage including hydraulic fracture(s) that are most likely to be the origin of the corresponding pressure response at the monitor well. This is accomplished using the detected fracture hits from block 206 (along with the corresponding prepared pressure data from block 204), as well as reasonable velocity window (RVW) data input at block 210 and observation property data input at block 212. Such observation property data include (but are not limited to) information relating to the time interval during which the hydraulic fracturing of each treatment stage was performed (since the corresponding pressure response will be observed at the monitor well concurrently with the treatment and/or soon after the treatment ends), the distance between the respective monitor well and each treatment stage along the expected fracture azimuth (which can be approximated as the direction of the maximum horizontal stress), and the completion intensity for each treatment stage. This information may be captured by a range of different fracture hit properties which are calculated relatively to the properties of the originating treatment stage, including (but not limited to) the volume to first response (VFR) (i.e., the volume of completion fluid pumped before a pressure response is observed at the monitor well), the time to first response (TFR) (i.e., the duration between the start of the treatment and the onset of the pressure response), the fracture hit velocity, the distance between the treatment stage and the monitor well along the expected fracture azimuth, and/or the amplitude of the pressure response.

According to embodiments described herein, treatment stage assignment at block 208 includes first detecting potential treatment stage assignments for each fracture hit based on the reasonable velocity window for fracture propagation in the subsurface. The reasonable velocity window is informed by prior offset pressure monitoring experiments in various basins. Treatment stage assignment is then automatically performed for any and all fracture hits that only have one likely option for the treatment stage of origin. The remaining treatment stages are then assigned to fracture hits using a data-driven process of elimination that is based, at least in part, on the observation property data, including (in particular) property data corresponding to treatment stages that have already been assigned to a particular fracture hit. More specifically, when competing treatment stage assignments exist for a single fracture hit, the treatment stage properties for each potential originating treatment stage are compared to treatment stage properties for treatment stages that have already been assigned to fracture hits (as described further with respect to FIG. 5, for example), and the treatment stage with the maximum probability of being the originating treatment stage (e.g., as measured via the greatest similarity in VFR, TFR, or the like) is then assigned to the fracture hit.

The following is a detailed description of an exemplary implementation of treatment stage assignment at block 208. However, those skilled in the art will appreciate that block 208 can alternatively be performed in any other suitable manner without departing from the scope of the present techniques. Turning to the details of such exemplary implementation, the treatment stage assignment includes two steps. The first step includes eliminating non-viable originating treatment stages, meaning that treatment stages which are too distantly located from the particular monitor well are automatically excluded from consideration. Possible treatment stage assignments are then identified for the detected fracture hits using a reasonable velocity window and a reasonable TFR ratio (e.g., a TFR ratio of less than 2.5) (where the term “TFR ratio” refers to the ratio of the TFR to the stage duration). (However, those skilled in the art will appreciate that a reasonable VFR ratio (where the term “VFR ratio” refers to the ratio of the VFR to the total volume pumped for the stage) or any other suitable property (other than the TFR ratio) may alternatively be utilized in other exemplary implementations.)

During the second step, a data-driven process of elimination is executed to assign treatment stages to the fracture hits, proceeding in the order of easiest to assign to hardest to assign. First, a pool of possible treatment stage assignments are determined, and treatment stage properties are computed for each possible fracture hit. Next, each fracture hit undergoes a process of elimination including multiple tests and several iterative loops (e.g., in some embodiments, five loops), resulting in the identification of a final treatment stage assignment for each fracture hit. In each loop, the tests below are performed iteratively; if the fracture hit fails all tests, it is saved for the next loop. Therefore, straightforward treatment stage assignments are identified during the first loops, thus reducing the list of available treatment stage assignments for all the other fracture hits in the following loops (i.e., proceeding from easiest to assign to hardest to assign). On the other hand, a probabilistic assignment test (described below) is only performed in the final loops, after the easiest to assign fracture hits have already been removed from consideration, and the information gained from the already-assigned treatment stages can be used in a probabilistic-based approach.

Turning to examples of specific tests that are conducted during the process of elimination, an initial test includes searching the unassigned fracture hits. Then, fracture hits with only one possible stage of origin are assigned. In other words, treatment stages are assigned to fracture hits for which only one likely treatment stage of origin was identified based on the RVW.

In another test, fracture hits are assigned to treatment stages that meet the criteria of a large pressure increase of, for example, greater than a given value in pounds per square inch (psi), with a pressure fall-off that immediately follows the end of the treatment (i.e., the maximum pressure is reached within minutes following the end of the treatment and the second derivative at maximum pressure time is negative). In another test, fracture hits are assigned for cases in which all competing fracture hit options for the treatment stage have already been assigned to another treatment stage.

In the final loops, after the easiest to assign fracture hits have already been removed from consideration, a data-driven probabilistic assignment test is performed. During the probabilistic assignment test, a probabilistic clustering technique is introduced to assign treatment stages to the remaining fracture hits based on the information gained from the already-assigned treatment stages (e.g., as determined, at least in part, by the corresponding observation property data, as described further with respect to FIG. 5, for example). This probabilistic clustering technique may include: (1) if there are no other possible assignments and only one treatment well has already been assigned fracture hits, a treatment stage from that well is selected; otherwise, a Gaussian Naïve Bayes classifier is used with properties from already-assigned fracture hits (e.g. VFR, VFR ratio, velocity, or the like) to predict the probability that the unassigned fracture hit belongs to each possible treatment stage, and using the classifier, all treatment stages with a probability lower than the highest probability assignment by more than a specified probability value of, for example, 5% are eliminated; (2) if only one option remains (e.g., because the difference in probability between the most likely assignment and the next best option is greater than 5%), the fracture hit is assigned; (3) if two or more options remain (e.g., because the highest probability assignments have probabilities within 5% of one another), proceed to another loop to attempt to break the tie after more stages have been assigned in the current loop; and (4) if breaking the tie proves impossible after the iterative process is over and the final loop has completed, retain all remaining options as equally likely.

FIG. 4 includes a first graph 400 showing measured pressure data from a monitor well (along with the detected fracture hits), as well as a second graph 402 depicting likely originating treatment stages for each fracture hit in the first graph 400. A first curve 404 in the first graph 400 represents the pressure data measured by the monitor well. A second curve 406 in the first graph 400 represents the second derivative of the pressure data. In addition, detected fracture hits (e.g., as determined by the observed pressure responses) are represented by pressure response lines 408A, 408B, 408C, 408D, 408E, 408F, 408G, 408H, and 408I that are each identified by a respective time stamp corresponding to the measured pressure data.

Turning to the second graph 402, bar graphs 410A-B, 412A-C, 414A-C, and 416A-C corresponding to the hydraulic fracturing of four treatment wells are depicted, with each treatment well being considered as a potential origin for the fracture hits 408A-I in the first graph 400. (Notably, in the bar graphs, a change in pattern indicates a change in bench.) Specifically, the bar graphs corresponding to each treatment well (e.g., bar graphs 410A-B, bar graphs 412A-C, bar graphs 414A-C, and bar graphs 416A-C, respectively) are labeled by stage number for the corresponding treatment well, and such bar graphs 410A-B, 412A-C, 414A-C, and 416A-C depict the stimulation times of such treatment stages, organized on the y-axis by average three-dimensional distance from the monitor well (where the more densely-shaded region of each bar graph represents the actual time of pumping and the less densely-shaded region of each bar graph encompasses the remainder of the reasonable velocity window for when a pressure response at the monitor well could be expected).

Now considering the first graph 400 in light of the second graph 402, it is apparent that the fracture hits corresponding to the second and sixth pressure response lines 404B and 404F, respectively, only have a single potential treatment stage assignment, i.e., the fourteenth stage of the first treatment well, as represented by bar graph 410A, and the fifteenth stage of the first treatment well, as represented by bar graph 410B, respectively. However, the fracture hits corresponding to the other pressure response lines 404A, 404C, 404D, 404E, 404G, 404H, and 404I each include more than one potential originating treatment stage, as shown in the second graph 402. Therefore, the reasonable velocity window shown in the second graph 402, in combination with the observation property data and the data-driven monitor-centric approach described herein, can be utilized to determine the treatment stages that are most likely to be the origin of each fracture hit. In the example shown in FIG. 4, for example, it may be determined that the fracture hit corresponding to the first pressure response line 404A should be assigned to the thirty-third stage of the fourth treatment well, as represented by bar graph 416A; the fracture hit corresponding to the third pressure response line 404C should be assigned to the twelfth stage of the third treatment well, as represented by bar graph 414B; the fracture hit corresponding to the fourth pressure response line 404D should be assigned to the thirty-fourth stage of the fourth treatment well, as represented by bar graph 416B; the fracture hit corresponding to the fifth pressure response line 404E should be assigned to the seventh stage of the second treatment well, as represented by bar graph 412B; the fracture hit corresponding to the seventh pressure response line 404G should be assigned to the thirteenth stage of the third treatment well, as represented by bar graph 414C; the fracture hit corresponding to the eighth pressure response line 404H should be assigned to the thirty-fifth stage of the fourth treatment well, as represented by bar graph 416C; and the fracture hit corresponding to the ninth pressure response line 404I should be assigned to the eighth stage of the second treatment well, as represented by bar graph 412C.

FIG. 5 includes a collection of graphs 502-532 of several types of observation property data from two treatment wells including stages that have already been assigned to specific fracture hits. As described herein, such comparable observation property data are utilized, in combination with the measured pressure data and the reasonable velocity window data, to determine which treatment stage is most likely to be the origin of each detected fracture hit. Specifically, according to the exemplary embodiment shown in FIG. 5, the TFR ratio data, VFR ratio distance data (where the term “VFR ratio distance” refers to the ratio of the VFR to the three-dimensional distance between the stage of origin and the monitor well along the fracture hit azimuth), fracture hit velocity data, and VFR ratio data are plotted for a first treatment well (represented by hollow circular data points in FIG. 5) and a second treatment well (represented by solid circular data points in FIG. 5) that each include stages that have already been assigned to other detected fracture hits. The data-driven process of elimination described herein then utilizes the data represented by these graphs 502-532, in combination with the measured pressure data and the reasonable velocity window data, to determine the probability that a given fracture hit (whose properties are represented by the “X” in the graphs) originated from a treatment stage corresponding to the first treatment well or a treatment stage corresponding to the second treatment well. According to the embodiment shown in FIG. 5, it is clear that the given fracture hit is more likely to have originated from a treatment stage corresponding to the first treatment well since the “X” in each graph is located closest to the hollow circular data points corresponding to the already-assigned treatment stages of the first treatment well.

FIGS. 6A and 6B include a collection of graphs 600, 602, and 604 that represent a complex exemplary implementation of the present techniques for multiple treatment wells that are simultaneously fractured. Specifically, a first graph 600 shows measured pressure data from the monitor well (along with the detected fracture hits), a second graph 602 shows fluid volumes pumped for each treatment stage for which pressure data has been measured; and a third graph 604 shows possible originating treatment stages for each fracture hit in the first graph 600. Moreover, a first curve 606 in the first graph 600 represents the smoothed pressure data measured by the monitor well, and a second curve 608 in the first graph 600 represents the second derivative of the pressure data. In addition, detected fracture hits (e.g., as determined by the observed pressure responses) are represented by pressure response lines (which are depicted as vertical lines in the first graph 600), where each pressure response line is identified by a respective time stamp corresponding to the measured pressure data.

Turning to the third graph 604, multiple bar graphs corresponding to the hydraulic fracturing of eleven treatment wells from five different pads are depicted, with each treatment well including potential originating treatment stages for the fracture hits in the first graph 600. The bar graphs depict the stimulation times of the corresponding treatment stages, organized on the y-axis by average three-dimensional distance from the monitor well. (Notably, in the bar graphs, a change in pattern indicates a change in bench.) Moreover, as described with respect to FIGS. 6A and 6B, the reasonable velocity window and the observation property data and the data-driven monitor-centric approach described herein can be utilized to determine the treatment stages that are most likely to be the origin of each fracture hit according to embodiments described herein, particularly for pressure response lines corresponding to fracture hits that include more than one possible originating treatment stage.

FIG. 7 is a process flow diagram of an exemplary method 700 for monitor-centric interpretation of offset pressure monitoring measurements in accordance with the present techniques. The method 700 provides the practical application the monitor-centric pressure response interpretation techniques described herein to a particular hydrocarbon well system including multiple treatment wells that are being monitored via at least one monitor well during a hydraulic fracturing operation. Moreover, the method 700 may be executed, in part, by one or more computing systems including one or more processors, such as the exemplary cluster computing system described with respect to FIG. 8 (or any suitable variation(s) thereof). In various embodiments, such computing system(s) are positioned at the hydrocarbon field at which the relevant wells are located and form part of the overall hydrocarbon well system. For example, the computing system(s) may form part of a mobile command center for directing the operations performed with respect to such wells.

The exemplary method 700 begins at block 702 with the simultaneous hydraulic fracturing of treatment stages corresponding to multiple treatment wells within the vicinity of one or more monitor wells. In various embodiments, such hydraulic fracturing closely follows the pattern of routine hydraulic fracturing operations and does not require any extra sequencing or timing efforts to accommodate the method 700.

At block 704, pressure data are measured during the hydraulic fracturing of the treatment stages via one or more pressure gauges (e.g., one or more arrays of pressure gauges) positioned at the monitor well(s). Moreover, in various embodiments, such pressure data are then prepared by smoothing the pressure data and computing first and second derivatives of the pressure data. At block 706, pressure responses corresponding to fracture hits within the pressure data are detected. In various embodiments, this includes detecting substantially all the pressure responses corresponding to fracture hits within the pressure data of the monitor well(s), as well as computing relevant properties corresponding to the pressure response, such as the time, amplitude, and the like.

The method 700 then proceeds to block 708 with the determination of a reasonable velocity window for when hydraulic fracture(s) originating from each treatment stage are likely to affect the pressure data measured at the monitor well(s). In various embodiments, the reasonable velocity windows are determined by leveraging data from prior offset pressure monitoring experiments. At block 710, one or more treatment stages that are likely to be the origin of each detected fracture hit are identified based on the reasonable velocity windows. At block 712, for each fracture hit that only has one treatment stage that is likely to be the origin, the detected fracture hit is assigned to the treatment stage. At block 714, observation property data corresponding to at least a portion of the treatment stages that have been assigned to the fracture hits are determined. In various embodiments, the observation property data corresponding to each treatment stage may include (but are not limited to) first data relating to the time interval during which the hydraulic fracturing of the treatment stage was performed, second data relating to the distance between the respective monitor well and the treatment stage along the expected fracture azimuth, and/or third data relating to the completion intensity for the treatment stage. Moreover, in some embodiments, such first, second, and/or third data may include (but are not limited to) VFR data, TFR data, VFR ratio data, TFR ratio data, fracture hit velocity data, monitor well/treatment stage distance data, and/or pressure response amplitude data.

At block 716, the observation property data from block 714 are utilized to iteratively assign each remaining, unassigned detected fracture hit to one of the corresponding treatment stages that is likely to be the origin and has not yet been assigned to one of the fracture hits. In various embodiments, blocks 712, 714, and 716 are performed according to an iterative process including multiple loops that operate to assign the fracture hits in an order of easiest to assign to hardest to assign, as described herein. Moreover, in some embodiments, block 716 includes executing a data-driven probabilistic clustering technique that determines the probability that the fracture hit originated from each treatment stage identified as likely to be the origin and not yet assigned to one of the fracture hits, as well as assigning the fracture hit to one of the treatment stages only if a difference between a highest determined probability and a next highest determined probability is greater than around 5% (although this probability value may vary depending on the details of the particular implementation).

In some embodiments, the method 700 further includes detecting, for at least one of the multiple treatment wells, wetted fracture dimensions for the fracture hits that are assigned to the treatment stages corresponding to the treatment well based on the corresponding pressure response within the pressure data, as well as adjusting the completion plan for the treatment well based on the determined wetted (and inferred conductive) fracture dimensions. Moreover, in some embodiments, detecting the wetted fracture dimensions includes performing fracture diagnostic techniques to characterize the wetted fracture shapes and capture insights on fracture growth within the subsurface.

Those skilled in the art will appreciate that the exemplary method 700 of FIG. 7 is susceptible to modification without altering the technical effect provided by the present techniques. In practice, the exact manner in which the method 700 is implemented will depend, at least in part, on the details of the specific implementation. For example, in some embodiments, some of the blocks shown in FIG. 7 may be altered or omitted from the method 700, and/or new blocks may be added to the method 700, without departing from the scope of the present techniques. As an example, in some embodiments, the method 700 includes confirming the accuracy of the treatment stage assignments using radioactive tracers, well interface testing, or the like.

Moreover, in some embodiments, offset monitoring data other than pressure data are additionally or alternatively utilized to perform the method 700. As an example, such offset monitoring data may include Distributed Acoustic Sensing (DAS) fiber data. In such embodiments, the method 700 is modified such that any suitable type of monitoring equipment is used in addition (or alternatively) to the pressure gauge(s), and any suitable type(s) of monitoring responses corresponding to the fracture hits are detected within the offset monitoring data. In other words, embodiments described herein may be extended to scenarios in which other types of data are measured at the monitoring well(s), without departing from the spirit and scope of the present techniques.

FIG. 8 is a block diagram of an exemplary cluster computing system 800 that may be utilized to implement at least a portion of the present techniques. The exemplary cluster computing system 800 shown in FIG. 8 has four computing units 802A, 802B, 802C, and 802D, each of which may perform calculations for a portion of the present techniques. However, one of ordinary skill in the art will recognize that the cluster computing system 800 is not limited to this configuration, as any number of computing configurations may be selected. For example, a smaller analysis may be run on a single computing unit, such as a workstation, while a large calculation may be run on a cluster computing system 800 having tens, hundreds, or even more computing units.

The cluster computing system 800 may be accessed from any number of client systems 804A and 804B over a network 806, for example, through a high-speed network interface 808. The computing units 802A to 802D may also function as client systems, providing both local computing support and access to the wider cluster computing system 800.

The network 806 may include a local area network (LAN), a wide area network (WAN), the Internet, or any combinations thereof. Each client system 804A and 804B may include one or more non-transitory, computer-readable storage media for storing the operating code and program instructions that are used to implement at least a portion of the present techniques, as described further with respect to the non-transitory, computer-readable storage medium of FIG. 9. For example, each client system 804A and 804B may include a memory device 810A and 810B, which may include random access memory (RAM), read only memory (ROM), and the like. Each client system 804A and 804B may also include a storage device 812A and 812B, which may include any number of hard drives, optical drives, flash drives, or the like.

The high-speed network interface 808 may be coupled to one or more buses in the cluster computing system 800, such as a communications bus 814. The communication bus 814 may be used to communicate instructions and data from the high-speed network interface 808 to a cluster storage system 816 and to each of the computing units 802A to 802D in the cluster computing system 800. The communications bus 814 may also be used for communications among the computing units 802A to 802D and the cluster storage system 816. In addition to the communications bus 814, a high-speed bus 818 can be present to increase the communications rate between the computing units 802A to 802D and/or the cluster storage system 816.

In some embodiments, the one or more non-transitory, computer-readable storage media of the cluster storage system 816 include storage arrays 820A, 820B, 820C and 820D for the storage of models, data, visual representations, results (such as graphs, charts, and the like used to convey results obtained using the present techniques), code, and other information concerning the implementation of at least a portion of the present techniques. The storage arrays 820A to 820D may include any combinations of hard drives, optical drives, flash drives, or the like.

Each computing unit 802A to 802D includes at least one processor 822A, 822B, 822C and 822D and associated local non-transitory, computer-readable storage media, such as a memory device 824A, 824B, 824C and 824D and a storage device 826A, 826B, 826C and 826D, for example. Each processor 822A to 822D may be a multiple core unit, such as a multiple core central processing unit (CPU) or a graphics processing unit (GPU). Each memory device 824A to 824D may include ROM and/or RAM used to store program instructions for directing the corresponding processor 822A to 822D to implement at least a portion of the present techniques. Each storage device 826A to 826D may include one or more hard drives, optical drives, flash drives, or the like. In addition, each storage device 826A to 826D may be used to provide storage for models, intermediate results, data, images, or code used to implement at least a portion of the present techniques.

The present techniques are not limited to the architecture or unit configuration illustrated in FIG. 8. For example, any suitable processor-based device may be utilized for implementing at least a portion of the embodiments described herein, including (without limitation) personal computers, laptop computers, computer workstations, mobile devices, and multi-processor servers or workstations with (or without) shared memory. Moreover, the embodiments described herein may be implemented, at least in part, on application specific integrated circuits (ASICs) or very-large-scale integrated (VLSI) circuits. In fact, those skilled in the art may utilize any number of suitable structures capable of executing logical operations according to the embodiments described herein.

FIG. 9 is a block diagram of an exemplary non-transitory, computer-readable storage medium (or media) 900 that may be used for the storage of data and modules of program instructions for implementing at least a portion of the present techniques. The non-transitory, computer-readable storage medium 900 may include a memory device, a hard disk, and/or any number of other devices, as described herein. A processor 902 may access the non-transitory, computer-readable storage medium 900 over a bus or network 904. While the non-transitory, computer-readable storage medium 900 may include any number of modules for implementing the present techniques, in some embodiments, the non-transitory, computer-readable storage medium 900 includes a monitor-centric pressure response interpretation module 906 for performing at least a portion of the techniques described herein (and/or any suitable variations thereof).

In one or more embodiments, the present techniques may be susceptible to various modifications and alternative forms, such as the following embodiments as noted in paragraphs 1 to 21:

• • 1. A method for monitor-centric interpretation of offset pressure monitoring measurements, including: simultaneously hydraulic fracturing treatment stages corresponding to multiple treatment wells within a vicinity of at least one monitor well; measuring, via at least one pressure gauge positioned at the at least one monitor well, pressure data during the hydraulic fracturing of the treatment stages; detecting, via a computing system, pressure responses corresponding to fracture hits within the pressure data; determining a reasonable velocity window for when a hydraulic fracture originating from each treatment stage is likely to affect the pressure data measured at the at least one monitor well; identifying at least one treatment stage that is likely to be the origin of each detected fracture hit based on the reasonable velocity window; for each fracture hit that only has one treatment stage that is likely to be the origin, assigning the detected fracture hit to the treatment stage; determining observation property data corresponding to at least a portion of the treatment stages that have been assigned to the fracture hits; and iteratively assigning, based on the observation property data, each remaining, unassigned detected fracture hit to one of the corresponding treatment stages that is likely to be the origin and has not yet been assigned to one of the fracture hits.
  • 2. The method of paragraph 1, including executing the assignment of the fracture hits that only have one treatment stage that is likely to be the origin, the determination of the observation property data, and the iterative assignment of the remaining, unassigned detected fracture hits according to an iterative process including multiple loops that operate to assign the fracture hits in an order of easiest to assign to hardest to assign.
  • 3. The method of paragraph 1 or 2, including iteratively assigning each remaining, unassigned detected fracture hit to one of the corresponding treatment stages based on the observation property data by: executing a data-driven probabilistic clustering technique that determines a probability that the fracture hit originated from each treatment stage identified as likely to be the origin and not yet assigned to one of the fracture hits; and assigning the fracture hit to one of the treatment stages only if a difference between a highest determined probability and a next highest determined probability is greater than 5%.
  • 4. The method of any of paragraphs 1 to 3, further including, for at least one of the multiple treatment wells: detecting, based on the corresponding pressure response within the pressure data, wetted fracture dimensions for the fracture hits that are assigned to the treatment stages corresponding to the treatment well; and adjusting a completion plan for the treatment well based on the determined wetted fracture dimensions and inferred conductive fracture dimensions.
  • 5. The method of any of paragraphs 1 to 4, including determining the reasonable velocity windows by leveraging data from prior offset pressure monitoring experiments.
  • 6. The method of any of paragraphs 1 to 5, including, prior to detecting the pressure responses corresponding to the fracture hits within the pressure data, preparing the measured pressure data by: smoothing the pressure data; and computing a first derivative and a second derivative of the pressure data.
  • 7. The method of any of paragraphs 1 to 6, including determining at least a portion of the observation property data for the treatment stages that have been assigned to the fracture hits by determining at least one of: first data relating to a time interval during which the hydraulic fracturing of the treatment stage was performed; second data relating to a distance between a respective monitor well and the treatment stage along an expected fracture azimuth; or third data relating to a completion intensity for the treatment stage.
  • 8. The method of paragraph 7, where the at least one of the first data, the second data, or the third data include at least one of: VFR data; TFR data; VFR ratio data; TFR ratio data; fracture hit velocity data; monitor well/treatment stage distance data; or pressure response amplitude data.
  • 9. A hydrocarbon well system including: multiple treatment wells; at least one monitor well including at least one pressure gauge that measures pressure data during the simultaneous hydraulic fracturing of treatment stages corresponding to the treatment wells; and a computing system that is communicably coupled to the at least one monitor well. The computing system includes a processor and a non-transitory, computer-readable storage medium. The non-transitory, computer-readable storage medium includes program instructions that are executable by the processor to cause the processor to: detect pressure responses corresponding to fracture hits within the measured pressure data; determine a reasonable velocity window for when a hydraulic fracture originating from each treatment stage is likely to affect the pressure data measured at the at least one monitor well; identify at least one treatment stage that is likely to be the origin of each detected fracture hit based on the reasonable velocity windows; for each fracture hit that only has one treatment stage that is likely to be the origin, assign the detected fracture hit to the treatment stage; determine observation property data corresponding to at least a portion of the treatment stages that have been assigned to the fracture hits; and iteratively assign, based on the observation property data, each remaining, unassigned detected fracture hit to one of the corresponding treatment stages that is likely to be the origin and has not yet been assigned to one of the fracture hits.
  • 10. The hydrocarbon well system of paragraph 9, where the non-transitory, computer-readable storage medium includes program instructions that are executable by the processor to cause the processor to execute the assignment of the fracture hits that only have one treatment stage that is likely to be the origin, the determination of the observation property data, and the iterative assignment of the remaining, unassigned detected fracture hits according to an iterative process including multiple loops that operate to assign the fracture hits in an order of easiest to assign to hardest to assign.
  • 11. The hydrocarbon well system of paragraph 9 or 10, where the non-transitory, computer-readable storage medium includes program instructions that are executable by the processor to cause the processor to iteratively assign each remaining, unassigned detected fracture hit to one of the corresponding treatment stages that are likely to be the origin based on the observation property data by: executing a probabilistic clustering technique that determines a probability that the fracture hit corresponds to each treatment stage that is likely to be the origin; and assigning the fracture hit to one of the treatment stages only if a difference between a highest determined probability and a next highest determined probability is greater than 5%.
  • 12. The hydrocarbon well system of any of paragraphs 9 to 11, where the non-transitory, computer-readable storage medium includes program instructions that are executable by the processor to cause the processor to, for at least one of the multiple treatment wells: detect, based on the corresponding pressure response within the pressure data, wetted fracture dimensions for the fracture hits that are assigned to the treatment stages corresponding to the treatment well; and adjust a completion plan for the treatment well based on the determined wetted fracture dimensions and inferred conductive fracture dimensions.
  • 13. The hydrocarbon well system of any of paragraphs 9 to 12, where the non-transitory, computer-readable storage medium includes program instructions that are executable by the processor to cause the processor to determine the reasonable velocity windows by leveraging data from prior offset pressure monitoring experiments.
  • 14. The hydrocarbon well system of any of paragraphs 9 to 13, where the non-transitory, computer-readable storage medium includes program instructions that are executable by the processor to cause the processor to, prior to the detection of the pressure responses corresponding to the fracture hits within the pressure data, prepare the measured pressure data by: smoothing the pressure data; and computing a first derivative and a second derivative of the pressure data.
  • 15. The hydrocarbon well system of any of paragraphs 9 to 14, where the non-transitory, computer-readable storage medium includes program instructions that are executable by the processor to cause the processor to determine at least a portion of the observation property data for each of the at least the portion of the treatment stages that have been assigned to the fracture hits by determining at least one of: first data relating to a time interval during which the hydraulic fracturing of the treatment stage was performed; second data relating to a distance between a respective monitor well and the treatment stage along an expected fracture azimuth; or third data relating to a completion intensity for the treatment stage.
  • 16. A non-transitory, computer-readable storage medium of paragraph 16, including program instructions that are executable by a processor to cause the processor to: receive pressure data measured via at least one monitor well during simultaneous hydraulic fracturing of treatment stages corresponding to multiple treatment wells within a vicinity of the at least one monitor well; detect pressure responses corresponding to fracture hits within the pressure data; determine a reasonable velocity window for when a hydraulic fracture originating from each treatment stage is likely to affect the pressure data measured at the at least one monitor well; identify at least one treatment stage that is likely to be the origin of each detected fracture hit based on the reasonable velocity windows; for each fracture hit that only has one treatment stage that is likely to be the origin, assign the detected fracture hit to the treatment stage; determine observation property data corresponding to at least a portion of the treatment stages that have been assigned to the fracture hits; and iteratively assign, based on the observation property data, each remaining, unassigned detected fracture hit to one of the corresponding treatment stages that is likely to be the origin and has not yet been assigned to one of the fracture hits.
  • 17. The non-transitory, computer-readable storage medium of paragraph 16, including program instructions that are executable by the processor to cause the processor to execute the assignment of the fracture hits that only have one treatment stage that is likely to be the origin, the determination of the observation property data, and the iterative assignment of the remaining, unassigned detected fracture hits according to an iterative process including multiple loops that operate to assign the fracture hits in an order of easiest to assign to hardest to assign.
  • 18. The non-transitory, computer-readable storage medium of any of paragraph 16 or 17, including program instructions that are executable by the processor to cause the processor to iteratively assign each remaining, unassigned detected fracture hit to one of the corresponding treatment stages that are likely to be the origin based on the observation property data by: executing a data-driven probabilistic clustering technique that determines a probability that the fracture hit originated from each treatment stage identified as likely to be the origin and not yet assigned to one of the fracture hits; and assigning the fracture hit to one of the treatment stages only if a difference between a highest determined probability and a next highest determined probability is greater than 5%.
  • 19. The non-transitory, computer-readable storage medium of any of paragraphs 16 to 18, including program instructions that are executable by the processor to cause the processor to, for at least one of the multiple treatment wells: detect, based on the corresponding pressure response within the pressure data, wetted fracture dimensions for the fracture hits that are assigned to the treatment stages corresponding to the treatment well; and adjust a completion plan for the treatment well based on the determined wetted fracture dimensions and inferred conductive fracture dimensions.
  • 20. The non-transitory, computer-readable storage medium of any of paragraphs 16 to 19, including program instructions that are executable by the processor to cause the processor to determine at least a portion of the observation property data for each of the at least the portion of the treatment stages that have been assigned to the fracture hits by determining at least one of: first data relating to a time interval during which the hydraulic fracturing of the treatment stage was performed; second data relating to a distance between a respective monitor well and the treatment stage along an expected fracture azimuth; or third data relating to a completion intensity for the treatment stage.
  • 21. A method for monitor-centric interpretation of offset monitoring measurements, including: simultaneously hydraulic fracturing treatment stages corresponding to multiple treatment wells within a vicinity of at least one monitor well; measuring, via monitoring equipment positioned at the at least one monitor well, offset monitoring data during the hydraulic fracturing of the treatment stages; detecting, via a computing system, offset monitoring responses corresponding to fracture hits within the offset monitoring data; determining a reasonable velocity window for when a hydraulic fracture originating from each treatment stage is likely to affect the offset monitoring data measured at the at least one monitor well; identifying at least one treatment stage that is likely to be the origin of each detected fracture hit based on the reasonable velocity window; for each fracture hit that only has one treatment stage that is likely to be the origin, assigning the detected fracture hit to the treatment stage; determining observation property data corresponding to at least a portion of the treatment stages that have been assigned to the fracture hits; and iteratively assigning, based on the observation property data, each remaining, unassigned detected fracture hit to one of the corresponding treatment stages that is likely to be the origin and has not yet been assigned to one of the fracture hits.

While the embodiments described herein are well-calculated to achieve the advantages set forth, it will be appreciated that such embodiments are susceptible to modification, variation, and change without departing from the spirit thereof. In other words, the particular embodiments described herein are illustrative only, as the teachings of the present techniques may be modified and practiced in different but equivalent manners apparent to those skilled in the art having the benefit of the teachings herein. Moreover, the systems and methods illustratively disclosed herein may suitably be practiced in the absence of any element that is not specifically disclosed herein and/or any optional element disclosed herein. While compositions and methods are described in terms of “comprising” or “including” various components or steps, the compositions and methods can also “consist essentially of” or “consist of” the various components and steps. Indeed, the present techniques include all alternatives, modifications, and equivalents falling within the true spirit and scope of the appended claims.

Claims

1. A method for monitor-centric interpretation of offset pressure monitoring measurements, comprising:

simultaneously hydraulic fracturing treatment stages corresponding to multiple treatment wells within a vicinity of at least one monitor well;

measuring, via at least one pressure gauge positioned at the at least one monitor well, pressure data during the hydraulic fracturing of the treatment stages;

detecting, via a computing system, pressure responses corresponding to fracture hits within the pressure data;

determining a reasonable velocity window for when a hydraulic fracture originating from each treatment stage is likely to affect the pressure data measured at the at least one monitor well;

identifying at least one treatment stage that is likely to be the origin of each detected fracture hit based on the reasonable velocity window;

for each fracture hit that only has one treatment stage that is likely to be the origin, assigning the detected fracture hit to the treatment stage;

determining observation property data corresponding to at least a portion of the treatment stages that have been assigned to the fracture hits; and

iteratively assigning, based on the observation property data, each remaining, unassigned detected fracture hit to one of the corresponding treatment stages that is likely to be the origin and has not yet been assigned to one of the fracture hits.

2. The method of claim 1, comprising executing the assignment of the fracture hits that only have one treatment stage that is likely to be the origin, the determination of the observation property data, and the iterative assignment of the remaining, unassigned detected fracture hits according to an iterative process comprising multiple loops that operate to assign the fracture hits in an order of easiest to assign to hardest to assign.

3. The method of claim 1, comprising iteratively assigning each remaining, unassigned detected fracture hit to one of the corresponding treatment stages based on the observation property data by:

executing a data-driven probabilistic clustering technique that determines a probability that the fracture hit originated from each treatment stage identified as likely to be the origin and not yet assigned to one of the fracture hits; and

assigning the fracture hit to one of the treatment stages only if a difference between a highest determined probability and a next highest determined probability is greater than 5%.

4. The method of claim 1, further comprising, for at least one of the multiple treatment wells:

detecting, based on the corresponding pressure response within the pressure data, wetted fracture dimensions for the fracture hits that are assigned to the treatment stages corresponding to the treatment well; and

adjusting a completion plan for the treatment well based on the determined wetted fracture dimensions and inferred conductive fracture dimensions.

5. The method of claim 1, comprising determining the reasonable velocity windows by leveraging data from prior offset pressure monitoring experiments.

6. The method of claim 1, comprising, prior to detecting the pressure responses corresponding to the fracture hits within the pressure data, preparing the measured pressure data by:

smoothing the pressure data; and

computing a first derivative and a second derivative of the pressure data.

7. The method of claim 1, comprising determining at least a portion of the observation property data for each of the at least the portion of the treatment stages that have been assigned to the fracture hits by determining at least one of:

first data relating to a time interval during which the hydraulic fracturing of the treatment stage was performed;

second data relating to a distance between a respective monitor well and the treatment stage along an expected fracture azimuth; or

third data relating to a completion intensity for the treatment stage.

8. The method of claim 7, wherein the at least one of the first data, the second data, or the third data comprise at least one of:

volume to first response (VFR) data;

time to first response (TFR) data;

VFR ratio data;

TFR ratio data;

fracture hit velocity data;

monitor well/treatment stage distance data; or

pressure response amplitude data.

9. A hydrocarbon well system, comprising:

multiple treatment wells;

at least one monitor well, comprising at least one pressure gauge that measures pressure data during the simultaneous hydraulic fracturing of treatment stages corresponding to the treatment wells; and

a computing system that is communicably coupled to the at least one monitor well, wherein the computing system comprises: a processor; and a non-transitory, computer-readable storage medium comprising program instructions that are executable by the processor to cause the processor to: detect pressure responses corresponding to fracture hits within the measured pressure data; determine a reasonable velocity window for when a hydraulic fracture originating from each treatment stage is likely to affect the pressure data measured at the at least one monitor well; identify at least one treatment stage that is likely to be the origin of each detected fracture hit based on the reasonable velocity windows; for each fracture hit that only has one treatment stage that is likely to be the origin, assign the detected fracture hit to the treatment stage; determine observation property data corresponding to at least a portion of the treatment stages that have been assigned to the fracture hits; and iteratively assign, based on the observation property data, each remaining, unassigned detected fracture hit to one of the corresponding treatment stages that is likely to be the origin and has not yet been assigned to one of the fracture hits.

10. The hydrocarbon well system of claim 9, wherein the non-transitory, computer-readable storage medium comprises program instructions that are executable by the processor to cause the processor to execute the assignment of the fracture hits that only have one treatment stage that is likely to be the origin, the determination of the observation property data, and the iterative assignment of the remaining, unassigned detected fracture hits according to an iterative process comprising multiple loops that operate to assign the fracture hits in an order of easiest to assign to hardest to assign.

11. The hydrocarbon well system of claim 9, wherein the non-transitory, computer-readable storage medium comprises program instructions that are executable by the processor to cause the processor to iteratively assign each remaining, unassigned detected fracture hit to one of the corresponding treatment stages that are likely to be the origin based on the observation property data by:

executing a data-driven probabilistic clustering technique that determines a probability that the fracture hit originated from each treatment stage identified as likely to be the origin and not yet assigned to one of the fracture hits; and

assigning the fracture hit to one of the treatment stages only if a difference between a highest determined probability and a next highest determined probability is greater than 5%.

12. The hydrocarbon well system of claim 9, wherein the non-transitory, computer-readable storage medium comprises program instructions that are executable by the processor to cause the processor to, for at least one of the multiple treatment wells:

detect, based on the corresponding pressure response within the pressure data, wetted fracture dimensions for the fracture hits that are assigned to the treatment stages corresponding to the treatment well; and

adjust a completion plan for the treatment well based on the determined wetted fracture dimensions and inferred conductive fracture dimensions.

13. The hydrocarbon well system of claim 9, wherein the non-transitory, computer-readable storage medium comprises program instructions that are executable by the processor to cause the processor to determine the reasonable velocity windows by leveraging data from prior offset pressure monitoring experiments.

14. The hydrocarbon well system of claim 9, wherein the non-transitory, computer-readable storage medium comprises program instructions that are executable by the processor to cause the processor to, prior to the detection of the pressure responses corresponding to the fracture hits within the pressure data, prepare the measured pressure data by:

smoothing the pressure data; and

computing a first derivative and a second derivative of the pressure data.

15. The hydrocarbon well system of claim 9, wherein the non-transitory, computer-readable storage medium comprises program instructions that are executable by the processor to cause the processor to determine at least a portion of the observation property data for each of the at least the portion of the treatment stages that have been assigned to the fracture hits by determining at least one of:

first data relating to a time interval during which the hydraulic fracturing of the treatment stage was performed;

second data relating to a distance between a respective monitor well and the treatment stage along an expected fracture azimuth; or

third data relating to a completion intensity for the treatment stage.

16. A non-transitory, computer-readable storage medium comprising program instructions that are executable by a processor to cause the processor to:

receive pressure data measured via at least one monitor well during simultaneous hydraulic fracturing of treatment stages corresponding to multiple treatment wells within a vicinity of the at least one monitor well;

detect pressure responses corresponding to fracture hits within the pressure data;

determine a reasonable velocity window for when a hydraulic fracture originating from each treatment stage is likely to affect the pressure data measured at the at least one monitor well;

identify at least one treatment stage that is likely to be the origin of each detected fracture hit based on the reasonable velocity windows;

for each fracture hit that only has one treatment stage that is likely to be the origin, assign the detected fracture hit to the treatment stage;

determine observation property data corresponding to at least a portion of the treatment stages that have been assigned to the fracture hits; and

iteratively assign, based on the observation property data, each remaining, unassigned detected fracture hit to one of the corresponding treatment stages that is likely to be the origin and has not yet been assigned to one of the fracture hits.

17. The non-transitory, computer-readable storage medium of claim 16, comprising program instructions that are executable by the processor to cause the processor to execute the assignment of the fracture hits that only have one treatment stage that is likely to be the origin, the determination of the observation property data, and the iterative assignment of the remaining, unassigned detected fracture hits according to an iterative process comprising multiple loops that operate to assign the fracture hits in an order of easiest to assign to hardest to assign.

18. The non-transitory, computer-readable storage medium of claim 16, comprising program instructions that are executable by the processor to cause the processor to iteratively assign each remaining, unassigned detected fracture hit to one of the corresponding treatment stages that are likely to be the origin based on the observation property data by:

executing a data-driven probabilistic clustering technique that determines a probability that the fracture hit originated from each treatment stage identified as likely to be the origin and not yet assigned to one of the fracture hits; and

assigning the fracture hit to one of the treatment stages only if a difference between a highest determined probability and a next highest determined probability is greater than 5%.

19. The non-transitory, computer-readable storage medium of claim 16, comprising program instructions that are executable by the processor to cause the processor to, for at least one of the multiple treatment wells:

detect, based on the corresponding pressure response within the pressure data, wetted fracture dimensions for the fracture hits that are assigned to the treatment stages corresponding to the treatment well; and

adjust a completion plan for the treatment well based on the determined wetted fracture dimensions and inferred conductive fracture dimensions.

20. The non-transitory, computer-readable storage medium of claim 16, comprising program instructions that are executable by the processor to cause the processor to determine at least a portion of the observation property data for each of the at least the portion of the treatment stages that have been assigned to the fracture hits by determining at least one of:

first data relating to a time interval during which the hydraulic fracturing of the treatment stage was performed;

second data relating to a distance between a respective monitor well and the treatment stage along an expected fracture azimuth; or

third data relating to a completion intensity for the treatment stage.