Method and system for determining an optimum pumping schedule corresponding to an optimum return on investment when fracturing a formation penetrated by a wellbore
A new method for determining a pumping schedule that will produce an acceptable return on investment for a particular well includes selecting a pumping schedule, which includes an initial pumping schedule and a remaining pumping schedule, adapted for fracturing a formation around one or more perforations in the particular well. Using the initial pumping schedule, interrogate a pump data model to produce a set of fracture characteristics. A set of tiltmeter sensors and micro-seismic sensors placed adjacent the fracture in the formation will also generate a set of fracture characteristics. If the set of fracture characteristics originating from the pump data model do not substantially match the set of fracture characteristics originating from the tiltmeter sensors and the micro-seismic sensors, the pump data model must be calibrated. When the pump data model is calibrated, use the remaining pumping schedule to interrogate the calibrated pump data model thereby producing a production rate and a return on investment corresponding to the production rate. If the return on investment is not an “optimum” return on investment, change either the proportions of frac fluid and proppant in the remaining pumping schedule or the viscosity of the fluid or the injection rate until a new remaining pumping schedule is determined. When the new remaining pumping schedule interrogates the calibrated pump data model, hopefully an “optimum” production rate and an “optimum” return on investment will be determined for the particular well. The owner of the particular well or other field engineers or other decision-making personnel will then consider the “optimum” return on investment before using the remaining pumping schedule to continue fracturing the formation around the perforations in the wellbore.
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This application claims benefit of U.S. Provisional Patent Application No. 60/481,623 filed on Nov. 11, 2003.
BACKGROUND OF INVENTIONThe subject matter of the present invention relates to a system and method for real time control of hydraulic fracturing treatments of a formation penetrated by a wellbore, and, in particular, a system and method for determining an optimum pumping schedule which corresponds to an optimum production rate and an optimum return on investment when fracturing a perforated formation penetrated by a wellbore.
When fracturing a formation penetrated by a wellbore, a particular pumping schedule is utilized for pumping fracturing fluid into a plurality of perforations in a formation penetrated by the wellbore. Oil and other hydrocarbon deposits will produce from the fractured perforations in response thereto, the oil and other hydrocarbon deposits flowing uphole. A particular production rate corresponds to the particular pumping schedule, the particular production rate representing the rate at which the oil and other hydrocarbon deposits flow uphole. A particular return on investment corresponds to the particular production rate of the hydrocarbon deposits flowing uphole, the particular return on investment representing the amount of a client's profits being derived from a producing well in connection with the particular production rate of the oil and other hydrocarbon deposits being produced from the well and flowing uphole in relation to the costs for fracturing and producing that well.
A client will want to know whether a particular return on investment, associated with a particular production rate and a particular pumping schedule for a single well is an “optimum” one. The term “optimum” is defined by the client. Therefore, it is desirable to determine in advance for a particular well, before a fracturing operation is completed, whether a selected pumping schedule is an “optimum” pumping schedule which, when utilized, will fracture a well in a particular manner such that oil and other hydrocarbon deposits will be produced at an “optimum” production rate thereby generating an “optimum” return on investment for the client.
SUMMARY OF INVENTIONOne aspect of the invention involves a method of determining a pumping schedule adapted for fracturing a formation penetrated by a wellbore, comprising the steps of: defining a selected pumping schedule to include an initial portion and a remaining portion; interrogating a pump data model in response to at least one of the initial portion and the remaining portion thereby generating a return on investment; deciding if the return on investment is an acceptable return on investment; and determining the pumping schedule to be the initial portion and the remaining portion of the selected pumping schedule when the return on investment is an acceptable return on investment.
Another aspect of the present invention involves a method of determining a pumping schedule corresponding to a particular return on investment for a particular wellbore, the pumping schedule including an initial pumping schedule and a remaining pumping schedule, comprising the steps of: (a) fracturing one or more perforations in a formation penetrated by the particular wellbore, thereby creating one or more fractures in the formation, in accordance with the initial pumping schedule; (b) analyzing a set of fracture characteristics associated with the one or more fractures in response to the fracturing step; (c) interrogating a pump data model in accordance with the remaining pumping schedule; and (d) determining a particular return on investment for the particular wellbore in response to the interrogating step, the pumping schedule corresponding to the particular return on investment for the particular wellbore when the pump data model is interrogated in accordance with the remaining pumping schedule.
Another aspect of the present invention involves a method of determining a return on investment associated with a particular wellbore before completing a fracturing of a formation penetrated by the wellbore, the formation being fractured in response to a particular pumping schedule, a pump data model generating one or more values indicative of the return on investment when interrogated by at least a portion of the pumping schedule, the method comprising the steps of: (a) before completing the fracturing of the formation, interrogating the pump data model in response to at least a portion of the pumping schedule; and (b) generating one or more values indicative of the return on investment in response to the interrogating step.
Another aspect of the present invention involves a method of determining a return on investment associated with a particular wellbore before completing a fracturing of a formation penetrated by the wellbore, the formation being fractured in response to a particular pumping schedule, a pump data model generating one or more values indicative of the return on investment when interrogated by at least a portion of the pumping schedule, the method comprising the steps of: (a) calibrating the pump data model; (b) before completing the fracturing of the formation, interrogating the calibrated pump data model in response to at least a portion of the pumping schedule; and (c) generating one or more values indicative of the return on investment in response to the interrogating step.
Another aspect of the present invention involves a method of determining a pumping schedule adapted for fracturing a formation penetrated by a wellbore, the pumping schedule including an initial pumping schedule and a remaining pumping schedule, comprising the steps of: (a) fracturing the formation penetrated by the wellbore in accordance with the initial pumping schedule thereby generating fractures in said formation; (b) interrogating a pump data model in response to the remaining pumping schedule thereby generating a return on investment; (c) in response to the interrogating step, deciding whether the return on investment is an acceptable return on investment; and (d) in response to the deciding step, determining the pumping schedule to be the initial pumping schedule and the remaining pumping schedule when the return on investment is an acceptable return on investment.
Further scope of applicability of the present invention will become apparent from the detailed description presented hereinafter. It should be understood, however, that the detailed description and the specific examples, while representing a preferred embodiment of the present invention, are given by way of illustration only, since various changes and modifications within the spirit and scope of the invention will become obvious to one skilled in the art from a reading of the following detailed description.
BRIEF DESCRIPTION OF DRAWINGSA full understanding of the present invention will be obtained from the detailed description of the preferred embodiment presented hereinbelow, and the accompanying drawings, which are given by way of illustration only and are not intended to be limitative of the present invention, and wherein:
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Now that the “pump data model” 60c2 is properly calibrated, the “remaining pumping schedule” 34b of
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However, if the aforementioned production rate of step 84 in
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A functional description of the operation of the present invention will be set forth in the following paragraphs with reference to
The present invention pertains to a method and system for determining an optimum pumping schedule corresponding to an optimum return on investment when fracturing a formation penetrated by a wellbore. A pumping schedule is selected for pumping fracturing fluid into a plurality of perforations in a formation penetrated by a wellbore. When the formation is fractured, a production rate and a return on investment is determined for the particular well. However, that production rate and return on investment is a function of the pumping schedule selected. If an “optimum” pumping schedule is selected for fracturing the plurality of perforations in the formation penetrated by the wellbore, an “optimum” production rate (i.e., the rate at which the oil or other hydrocarbon deposits are produced from the fractured perforations) is produced and, as a result, an “optimum” return on investment is the result, where the term “optimum” is determined by the owner of the wellbore. The “optimum” pumping schedule has been determined by selecting a plurality of pumping schedules for a respective plurality of wellbores and, after fracturing the perforations in those plurality of wellbores, eventually determining the “optimum” pumping schedule that corresponds to the “optimum” return on investment”. However, a plurality of wellbores are utilized during the above-referenced practice of determining the “optimum” pumping schedule that corresponds to the “optimum” return on investment.
A better method (for determining an “optimum” pumping schedule that corresponds to an “optimum” production rate and an “optimum” return on investment) would involve determining the “optimum” pumping schedule that corresponds to the “optimum” return on investment for “one particular wellbore”, and not for a plurality of wellbores as previously described. According to this better method, a “particular pumping schedule” 34 is divided into an “initial pumping schedule” 34a and a “remaining pumping schedule” 34b; and “one particular wellbore” 36 is selected to be fractured in accordance with that “particular pumping schedule” 34. The Earth formation penetrated by the “one particular wellbore” 36 is perforated in the manner described above with reference to
Functional Specification for the Bottom Hole Sensors Answer Product Software 60c1
A functional specification associated with the “Bottom Hole Sensors Answer Product Software” 60c1 of
User interactions are performed through the Recorder or Display Device 60b in
Where the input device is a touch screen, the input device and the terminal screen are the same thing.
Timeline merging (56 in
1. The pump parameters are treated as the Primary Source, this serves as the timeline for the merged dataset.
2. All other sources (e.g. microseismic, tiltmeter, bottom hole pressure, temperature etc.) are considered as Secondary Sources.
3. Data from Secondary Sources is intially buffered.
4. The time location for an observation in the Secondary Source is read from the buffer.
5. The corresponding time is located in the Primary Source
6. The information from the Secondary Source buffer is appended to the Primary Source information at the correct time, creating the Merged Data Set.
7. This operates continuously during real-time data acquisition so that the Merged Data is continuously available for processing.
8. If Secondary Source data appears with timestamps more recent than the more recent Primary Source data, it is buffered until needed.
9. If the Primary Source ends (or fails), one of the Secondary Sources will be selected, by the user, to become the Primary Source so that data-merging can continue.
Pump Data Model Fracture Characteristics (64 and 64a in
1. The forward model includes information on rock properties, such as Young's Modulus, in-situ stress, Poisson's Ratio, permeability, reservoir pressure etc.
2. There are multiple available fracture models (1-, 2- and 3-dimensional) and the user selects whichever is most appropriate for the current job.
3. This is a numerical model based on physical principles
4. The model is used to create predictions of the possible observables such as the examples listed in 64a of
5. These output predictions are stored ready for display along-side observations for comparison.
Tiltmeter Data Fracture Characteristics (66 in
1. An inversion algorithm is used to calculate the size and shape of the distortion that resulted in the tilt.
2. There are multiple such algorithms avialable and the user selects whichever is most appropriate for the current job.
Microseismic Data Fracture Characteristics (68 and 68a in
1. The user can view the microseismic event locations in three orthogonal two-dimensional views (East vs. North, North vs. Depth and East vs. Depth).
2. Interactively the user may draw a box around a sub-set of the microseismic points, relating to the hydraulic fracture.
3. The interpretation in step 2 allows the experienced user to differentiate microseismic events from the fracturing from, say, events generated by movement of an existing fault plane nearby.
4. The microseismic points lying inside a particular interpretation box are considered as an interpretation set.
5. For each interpretation set, the minimum-distance least-squares line through the points is considered to be the interpreted axis of the fracture.
6. The center of the fracture is considered to be located at the mean position of the microseismic events in the interpretation box.
7. The length of the fracture is determined by the furthest distance of a microseismic event along the interpreted axis in either direction.
8. The length is stored in each direction as a half-length, so that asymmetry of the fracture may be determined.
9. The height of the fracture is determined by the further distance of a microseismic event perpendicular to the axis along the minimum-distance least-squares plane through the points.
10. The height is stored in each direction from the center as a half-height, so that again symmetry can be analyzed.
11. The elliptical area of the fracture is determined from the length and height information.
12. The rectangular area of the fracture is determined from the length and height information.
13. The orientation of the fracture is determined as the orientation of the interpreted axis.
14. The fracture characteristics determined from the microseismic information are stored (by 60c in
Diagnostic Display (60b1 in
1. The diagnostic display is completely configurable in terms of which graphs are displayed.
2. The configuration for a particular job contains graphs that compare stored information. This can be observations, results from the Pump Data Model (64 and 64a in
3. The interaction for the user to intepret fracture characteristics from microseismic described above, can be achieved using a diagnostic plot.
4. Diagnostic plots can carry automatic alarms. These alarms can be triggered by any information trigger (for example greater-than, less-than a value; difference between modeled and observed values of the same property etc.) see 70 in
5. The alarms alert the user immediately to early-warning signals that the original operation is not producing the desired results.
6. Alarms can be set for any observation, any fracture characteristic derived from observation, or any model output.
7. Alarms can be created for any mathematical combination of the values described in step 6.
8. The Diagnostic Displays can show predictions based on the portion of the pump schedule not yet pumped.
9. The Diagnostic Displays can show results from production simulation and return on investment.
Calibration of the pump model (72, 74, 76 and 78 in
1. The user decides to perform a calibration, and so clicks on the “Calibrate” button to initiate the process.
2. The pump schedule is split into the fixed portion (that which has been pumped so far 34a in
3. Concentrating on the fixed portion, the user can further split the pumpshcedule into calibration intervals.
4. The user selects a match-point within each calibration interval (in time) where the obesrvations and the model will be compared.
5. The user selects the appropriate quantity (rock properties or friction of the proppant) to vary to achieve the match.
6. The program iteratively adjusts the appropriate quantity to improve the match at the define match-points until the root-mean-square difference between the modeled and measured values is below a user-defined limit. This is an iterative optimization.
7. Once the match is good as defined in step 6, the Pump Data Model is considered to be calibrated and useful for predictions.
Optimizing the remaining pump schedule
1. The fixed portion and remaining portion of the pump schedule (80 in
2. The output from the Pump Data Model includes a propped fracture length and a fracture conductivity. It is the fracture characteristics resulting from completing the current job with the remaining portion of the pump schedule (90 in
3. The fracture length and conductivity, along with rock properties are inputs to a production simulator (84 in
4. The production simulator is a numerical simulator that uses mass-balance and flow equations to model the predicted flow of hydrocarbons through the well during reservoir production.
5. There are several production simulators available and the user selects the most appropriate one for this job.
6. The production simulator uses specified well controls (for example a constant draw-down pressure) to numerically model the production expected from the fractured well.
7. The output of the production simulator is the production vs. time (commonly known as the Decline Curve (the “Production Rate” in 94 of
8. The outputs from the production simulator are forwarded to the Return On Investment calculation (86 in
9. The return on investment considers the cost of the fracture treatment and the monetary value of the decline curve, plus any costs associated with handling unwanted production (such as the water-cut). These are the known costs.
10. The return on investment simulator is a numerical simulator that provides a monetary value over time for the results of the fracturing.
11. There are several ways to calculated return on investment available. The user selects the most appropriate.
12. The return on investment provides an output of return versus time from the production data and the known costs. (96 on
13. An adjustment is made to the fluid and proppant pumped in the remaining portion of the pump schedule.
This is made under the constraint of the total materials available at the well-site minus the total materials pumped so far (102 on
14. Steps from 1 through 13 are repeated iteratively to improve the return on investment in line with the client's definition of an “optimum” return. (98 on
15. The remaining portion of the pump schedule that has been determined by the above scheme represents an optimum alternative to the original remaining portion of the pump schedule (104 in
16. A graphical display contrasts the return on investment for continuing with the original remaining portion or, instead, using the newly determined remaining portion.
17. The client is then able to select between the alternatives, and any changes are relayed to the pump operator.
18. This calibration and optimization scheme can be recalculated at any time during the job. The portion of fixed schedule being determined at the time the user begins to calibrate.
19. The calibration and optimization are rapid operations compared to the length of the pump schedule.
The invention being thus described, it will be obvious that the same may be varied in many ways. Such variations are not to be regarded as a departure from the spirit and scope of the invention, and all such modifications as would be obvious to one skilled in the art are intended to be included within the scope of the following claims.
Claims
1. A method of determining a pumping schedule adapted for fracturing a formation penetrated by a wellbore, comprising the steps of:
- defining a selected pumping schedule to include an initial portion and a remaining portion;
- interrogating a pump data model in response to at least one of said initial portion and said remaining portion thereby generating a return on investment;
- deciding if said return on investment is a particular return on investment; and
- determining said pumping schedule to be said initial portion and said remaining portion of said selected pumping schedule when said return on investment is said particular return on investment.
2. A method of determining a pumping schedule corresponding to a particular return on investment for a particular wellbore, the pumping schedule including an initial pumping schedule and a remaining pumping schedule, comprising the steps of:
- (a) fracturing one or more perforations in a formation penetrated by the particular wellbore, thereby creating one or more fractures in said formation, in accordance with said initial pumping schedule;
- (b) analyzing a set of fracture characteristics associated with said one or more fractures in response to the fracturing step;
- (c) interrogating a pump data model in accordance with said remaining pumping schedule; and
- (d) determining a particular return on investment for said particular wellbore in response to the interrogating step, said pumping schedule corresponding to said particular return on investment for said particular wellbore being determined when said pump data model is interrogated in response to said remaining pumping schedule.
3. The method of claim 2, wherein the analyzing step (b) for analyzing a set of fracture characteristics associated with said one or more fractures in response to the fracturing step comprises the steps of:
- (b1) analyzing a set of fracture characteristics associated with said one or more fractures in response to the fracturing step; and
- (b2) calibrating a pump data model in response to the analyzing step (b1) thereby generating a calibrated pump data model.
4. The method of claim 3, wherein the interrogating step (c) for interrogating a pump data model in accordance with said remaining pumping schedule comprises the steps of:
- (c1) interrogating said calibrated pump data model in response to said remaining pumping schedule.
5. The method of claim 4, wherein the determining step (d) for determining a particular return on investment for said particular wellbore in response to the interrogating step comprises the step of:
- (d1) determining a particular return on investment for said particular wellbore in response to the step of interrogating said calibrated pump data model in response to said remaining pumping schedule, said pumping schedule corresponding to said particular return on investment for said particular wellbore being determined when said calibrated pump data model is interrogated in response to said remaining pumping schedule.
6. The method of claim 3, wherein the interrogating step (c) for interrogating a pump data model in accordance with said remaining pumping schedule comprises the steps of:
- (c1) changing a proportion of said frac fluid and said proppant in said remaining pumping schedule thereby generating a new remaining pumping schedule; and
- (c2) interrogating said calibrated pump data model in response to said new remaining pumping schedule.
7. The method of claim 6, wherein the determining step (d) for determining a particular return on investment for said particular wellbore in response to the interrogating step comprises the step of:
- (d1) determining a particular return on investment for said particular wellbore in response to the step of interrogating said calibrated pump data model in response to said new remaining pumping schedule, said pumping schedule corresponding to said particular return on investment for said particular wellbore being determined when said calibrated pump data model is interrogated in response to said new remaining pumping schedule.
8. A method of determining a return on investment associated with a particular wellbore before completing a fracturing of a formation penetrated by the wellbore, said formation being fractured in response to a particular pumping schedule, a pump data model generating one or more values indicative of said return on investment when interrogated by at least a portion of said pumping schedule, said method comprising the steps of:
- (a) before completing said fracturing of said formation, interrogating said pump data model in response to said at least a portion of said pumping schedule; and
- (b) generating one or more values indicative of said return on investment in response to the interrogating step.
9. The method of claim 8, wherein the interrogating step (a) further comprises the steps of:
- calibrating said pump data model; and
- before completing said fracturing of said formation, interrogating the calibrated pump data model in response to said at least a portion of said pumping schedule.
10. A method of determining a pumping schedule adapted for fracturing a formation penetrated by a wellbore, said pumping schedule including an initial pumping schedule and a remaining pumping schedule, comprising the steps of:
- (a) fracturing said formation penetrated by said wellbore in accordance with said initial pumping schedule thereby generating fractures in said formation;
- (b) interrogating a pump data model in response to said remaining pumping schedule thereby generating a return on investment;
- (c) in response to the interrogating step, deciding whether said return on investment is a particular return on investment; and
- (d) in response to the deciding step (c), determining said pumping schedule to be said initial pumping schedule and said remaining pumping schedule when said return on investment is said particular return on investment.
11. The method of claim 10, wherein the fracturing step (a) for fracturing said formation penetrated by said wellbore in accordance with said initial pumping schedule comprises the steps of:
- (a1) fracturing said formation penetrated by said wellbore in accordance with said initial pumping schedule;
- (a2) generating a set of fracture characteristics in response to the fracturing step (a1);
- (a3) analyzing said set of fracture characteristics; and
- (a4) calibrating a pump data model in response to the analyzing step (a3) thereby generating a calibrated pump data model.
12. The method of claim 11, wherein the interrogating step (b) for interrogating a pump data model comprises the step of:
- (b1) interrogating said calibrated pump data model in response to said remaining pumping schedule thereby generating a return on investment.
13. The method of claim 11, wherein the interrogating step (b) for interrogating a pump data model comprises the step of:
- (b1) changing a proportion of a frac fluid and a proppant in said remaining pumping schedule thereby generating a new remaining pumping schedule; and
- (b2) interrogating said calibrated pump data model in response to said new remaining pumping schedule thereby generating a return on investment.
14. The method of claim 11, wherein generating step (a2) for generating a set of fracture characteristics comprises the steps of:
- interrogating the pump data model in response to the initial pumping schedule thereby generating a set of pump data model fracture characteristics,
- generating a set of tiltmeter data fracture characteristics on the condition that a tiltmeter data sensor is located adjacent the fractures, and
- generating a set of micro-seismic data fracture characteristics on the condition that a micro-seismic data sensor is located adjacent the fractures.
15. The method of step 14, wherein the analyzing step (a3) for analyzing said set of fracture characteristics comprises the step of:
- determining whether said set of pump data model fracture characteristics substantially matches said set of tiltmeter data fracture characteristics and said set of micro-seismic data fracture characteristics.
16. The method of claim 15, wherein said pump data model is calibrated thereby generating said calibrated pump data model in response to the analyzing step (a3) when said set of pump data model fracture characteristics substantially matches said set of tiltmeter data fracture characteristics and said set of micro-seismic data fracture characteristics.
17. The method of claim 16, wherein the interrogating step (b) for interrogating a pump data model comprises the step of:
- (b1) interrogating said calibrated pump data model in response to said remaining pumping schedule thereby generating a return on investment.
18. The method of claim 16, wherein the interrogating step (b) for interrogating a pump data model comprises the step of:
- (b1) changing a proportion of a frac fluid and a proppant in said remaining pumping schedule thereby generating a new remaining pumping schedule; and
- (b2) interrogating said calibrated pump data model in response to said new remaining pumping schedule thereby generating a return on investment.
Type: Application
Filed: Feb 4, 2004
Publication Date: Jun 2, 2005
Applicant: Schlumberger Technology Corporation (Sugar Land, TX)
Inventors: Michael Williams (Houston, TX), Darren Rodgers (Katy, TX), Eduard Siebrits (Stafford, TX), Mark Mack (Houston, TX)
Application Number: 10/708,032