METHODS OF DETERMINING BOREHOLE CHARACTERISTICS

Abstract

A method of determining borehole characteristics comprises arranging at least one sensing fiber along a borehole, causing pressure changes in the borehole, and measuring strain along the sensing fiber to obtain strain data. The strain data obtained thereby can be interpreted, for example, to determine borehole fracture geometry and to determine borehole perforation cluster efficiency. These results can be used to improve well completion and stimulation designs, increase field production, and/or decrease costs.

Description

CROSS-REFERENCE TO RELATED APPLICATION

This application claims the benefit of Provisional U.S. Patent Application Ser. No. 62/705,078 filed on Jun. 10, 2020, the contents of which are incorporated herein by reference in their entireties for all purposes.

TECHNICAL FIELD

The present disclosure relates to a method of determining borehole characteristics, and more particularly, for example, for near-wellbore hydraulic fracture and perforation efficiency diagnosis using distributed sensing measurements.

BACKGROUND INFORMATION

Productions from unconventional reservoirs (e.g., shale, tight sandstone) play an important role in the energy market. The development of unconventional reservoirs was enabled by two key technologies: horizontal drilling and hydraulic fracturing. Horizontal drilling technology can horizontally deploy a borehole for tracking the targeted formation in the deep subsurface to increase the contact length to the reservoir. Hydraulic fracturing can generate hydraulic fractures in the target reservoir by injecting mixtures of water, chemicals, and proppant (fine-grain sand, ceramic, or other materials) into the reservoir with extremely high pressure. The generated hydraulic fractures can increase the effective permeability of the original tight (low-permeability) reservoir rocks, and can enhance the migration of hydrocarbons (oil and gas) within the reservoir. The hydraulic fracturing operation is usually referred to as reservoir stimulation, which is part of well completion procedures.

In order to improve production performance, the hydraulic fractures should be generated as evenly as possible in the reservoir. The wellbore portion within the reservoir is usually divided into small sections which are stimulated individually. Each section is referred to as a stage. Within a stage, several entry points to the reservoir are created in the wellbore, allowing the injected fluid to enter the reservoir and generate hydraulic fractures. The entry points are usually referred to as perforations or perforation clusters. That is, a perforation is the channel through which the pressure communicates between the near-wellbore hydraulic fracture system and the borehole. Hydraulic fractures will typically be initiated at the entry points and grow into the reservoir with complex geometry (see, e.g., Raterman et al. 2018), which is controlled by the reservoir rock property, reservoir stress condition, pre-existing geological structures, and hydraulic fracturing designs. Hydraulic fracturing designs can include, but are not limited to, variations in perforation cluster spacing, number of perforation cluster per stage, injection volume, injection rate, proppant concentration, injection fluid viscosity, injection chemical combination, etc.

During the production stage, hydrocarbons migrate from the rock matrix to the well through the created hydraulic fractures network, driven by the pressure gradient, with the borehole having the lowest pressure. As the pressure depletes due to production, the aperture (width) of hydraulic fractures decreases due to the pressure difference between the rock matrix and fluid within the fractures. The proppant injected during the pumping stage is designed to support the fracture aperture with its mechanical strength (see, e.g., Kurz et al. 2013) after the fracture aperture is reduced to a certain level. After this point, the fracture aperture still decreases with pressure due to the elastic deformation of proppant grains, but at a different rate compared to the fractures that are not supported by proppant.

Existing methods of field observations that can be used to constrain near-wellbore (i.e., <30 m from the well opening) fracture properties are quite limited. Many techniques have been developed to evaluate hydraulic fractures in the far field (>10 m away from the well), including microseismic monitoring (see Calvez et al. 2007; Baan et al. 2013; Maxwell et al. 2010), low-frequency strain monitoring (see, e.g., Jin and Roy 2017), core analysis (see Raterman et al. 2018), pressure analysis (see Seth et al. 2019), etc. More recently, special attention has been made to the near-field (near-wellbore) hydraulic fracture properties. Near-wellbore fracture properties heavily influence the well's production performance because all the produced hydrocarbons pass through this fracture network before entering the borehole through perforations. Laboratory and numerical modeling work has been done to understand the near-wellbore fracture properties (see Fallahzadeh et al. 2017; Dong and Tang 2019). However, very limited field observations can help to constrain the actual near-field fracture geometry. Raterman et al. (2018) used core extraction to analyze near-wellbore hydraulic fractures. However, this method requires drilling a horizontal monitor wellbore close and parallel to the stimulated well, which is extremely expensive, and exposed the risk of damaging existing wellbore. Ugueto et al. (2019) discusses using temperature warmback signal to constrain near-wellbore fracture geometry. However, temperature measurements can be affected by many factors, including cross-flow between perforations, far-field production fluid warming, near-field thermal diffusion, etc. Moreover, the borehole temperature signature diminishes after a certain period of production due to thermal conduction between wellbore fluid and reservoir rocks. As a result, this method cannot provide long-term, high-quality monitoring of near-wellbore fracture geometry and properties.

Moreover, current methods cannot efficiently evaluate perforation cluster efficiency for modern unconventional wells. Perforation efficiency is defined as the percentage of production contribution of the perforation or perforation cluster to the total production of the well. To actually evaluate perforation efficiency, a production logging operation (see Daniel Hill 1990) is typically needed. However, traditional production logging operation through well intervention in horizontal unconventional wells is quite challenging and expensive (see, e.g. Heddleston 2009; Miklashevskiy et al. 2017). Some recent developments have been made to explore non-intrusive production logging methods (see Ovchinnikov et al. 2017; Jin et al. 2019), but these methods suffer high-uncertainty and non-unique results. Moreover, all aforementioned production logging methods cannot provide results with a spatial resolution comparable to modern perforation cluster spacings (5-100 ft). Near-wellbore fracture properties are highly correlated with perforation efficiency. With a proper estimation of near-wellbore fracture properties, perforation cluster efficiency can be evaluated. More importantly, the relation between perforation cluster efficiency and hydraulic fracturing designs can be established in the same stimulation well to accelerate hydraulic fracturing design optimization in the reservoir development.

Distributed strain measurements have not been effectively taken in a producing well. There is a growing trend in the oil industry that utilizes Distributed Fiber-Optic Sensing (DFOS) technology to monitor and evaluate hydraulic fracturing operations and later production performance of unconventional wells. Current applications include perforation injection allocation (see, e.g. Boone et al. 2015), microseismic monitoring (see, e.g. Webster et al. 2013), and production logging (see, Jin et al. 2019). More recently, it has become popular to use Distributed Strain Sensing (DSS) to monitor mechanical strain variations for hydraulic fracturing monitoring (see Jin and Roy 2017). Typical DSS applications however focus on measurements from an offset monitor well (cross-well monitoring), instead of the actual producing well (in-well monitoring). As such, little near-wellbore fracture information can be obtained.

Furthermore, multiple physical effects cannot be separated in the measured DFOS data. When a DFOS method is used for near-wellbore deformation measurements, the fiber optic will subjected not only to strain, but also subjected to temperature, pressure and other physics variables. Due to the injection and production activities, the thermal strain induced by borehole temperature variations are usually larger or comparable to the interested mechanical strain signals, which is one of the main challenges to use DSS for in-well measurements.

The sensitivity and resolution of current DSS measurements are also limited. The mechanical strain variation during production period in the producing well is usually small and localized around the perforation locations. The sensitivity and spatial resolution of previous Brillouin-based (see, e.g., Hong et al. 2017) or low-frequency Distributed Acoustic Sensing (DAS) based (see, e.g., Jin and Roy 2017) DSS measurements are typically insufficient to capture the desired signal.

SUMMARY

A method of determining borehole characteristics is disclosed and comprises arranging at least one sensing fiber along a borehole which has been hydraulically fractured, causing pressure changes in the borehole, and measuring strain along the sensing fiber to obtain strain data.

BRIEF DESCRIPTION OF THE DRAWINGS

Other features and advantages disclosed herein will become more apparent from the following detailed description of illustrative embodiments when read in conjunction with the attached drawings.

FIG. 1 is a schematic representation of an illustrative method of determining borehole characteristics.

FIG. 2 is a schematic representation of an illustrative well operation and data acquisition sequence to diagnose near-wellbore fracture and perforation efficiency.

FIG. 3 is a schematic representation of an illustrative process of using distributed strain sensing to measure near-wellbore fracture geometry and property.

FIG. 4 is a schematic representation of illustrative strain data obtained from distributed strain sensing measurement of strain variation due to a shut-in operation on an unconventional oil producer, where black triangles depict perforation cluster locations, while a dashed horizontal line separates extension and compression zones.

FIG. 5 is a schematic representation of an illustrative comparison of strain variation at perforation clusters of two different hydraulic fracturing designs in the same unconventional well, where black dot and error bars show the mean and standard deviation of the strain variation of a given design.

DETAILED DESCRIPTION

Due to the complexity of fracture propagation processes and uncertainty of local rock properties and geological condition, the actual hydraulic fracture geometry and property can be quite difficult to predict by analytical or numerical models (see Raterman et al. 2018). Moreover, understanding the geometry and property of hydraulic fractures can also be quite helpful for optimizing the development of unconventional reservoirs. Different designs of fracturing operations could lead to various hydraulic fracturing and proppant transportation results (see Zeng and Guo 2016; Curnow and Tutuncu 2016), which can significantly affect the production performance during the later production period.

The present disclosure describes illustrative methods utilizing Distributed Temperature and Strain Sensing (DTSS) technology to evaluate near-wellbore fracture properties and perforation cluster efficiency, by measuring the in-well mechanical strain variations induced by borehole pressure changes.

Borehole pressure, which is defined as the fluid pressure inside the wellbore, can change dramatically due to such well operations as injection, production, and shut-in. During injection, borehole pressure is artificially increased by the pumping activity from the surface. During production, because hydrocarbon and water are extracted from the reservoir to the surface, either by the reservoir pressure or by artificial lift equipment, the borehole pressure slowly decreases overtime. During a shut-in operation, during which the well stops its original injection or production operation, borehole pressure also changes due to the pressure re-equilibrium process within the reservoir.

For wells that are hydraulically fractured, borehole pressure changes can also induce mechanical strain perturbation in the rock near the wellbore region. This is because of the permeability difference between the hydraulic fractures and reservoir rocks. Due to the low permeability within the hydraulic fractures, the change of borehole pressure can propagate much faster along the hydraulic fractures than into the formation rock matrix. This can change the pressure difference between the fluid within the fracture and the fluid in the pore space of the rock matrix (pore pressure). This pressure difference variation can change the fracture width, and can induce mechanical strain variation in regions within and near the hydraulic fractures. If a fiber is installed along the borehole, the mechanical strain variation can be measured using the aforementioned DSS technology.

One way of generating pressure-induced near-wellbore strain changes is to shut-in a well that is under stable production. During the stable production period, the pressure within the hydraulic fractures that are connected to the wellbore is lower than the pore pressure of the reservoir rock matrix. This pressure difference drives the hydrocarbon resource to flow from the rock matrix towards the borehole through the hydraulic fracture system. After the shut-in operation, the pressure within the hydraulic fractures increases to equalize with the rock matrix pore pressure, and fracture width increases due to less pressure gradient between the two.

FIG. 1 shows an illustrative process of using distributed strain sensing to measure near-wellbore fracture geometry and property due to borehole pressure changes. At least one sensing fiber 202 is inserted into a wellbore 204. Pressure changes within the wellbore 204 cause pressure changes at a hydraulic fracture 206 and perforation 208. As such, if the wellbore 204 pressure increases during the monitoring period, the measured DSS signal is expected to indicate a strong positive strain (extension) at the borehole locations adjoining the near-wellbore fractures, and weak negative strain nearby due to stress shadow effect (see Taghichian, Zaman, and Devegowda 2014). The shape and the magnitude of the strain signal are related to the geometry and property of near-wellbore fractures and perforation cluster efficiency.

Illustrative methods in accordance with the present disclosure can overcome difficulties associated with in-well DSS measurement. There are several methods available to obtain strain in a permanent casing conveyed sensing fiber:

(1) Utilizing DTSS technology to obtain the temperature value and then subtracting the temperature effects from Brillouin or Rayleigh frequency shifts. By this method, temperature spatial resolution is generally more approximative than obtaining strain data. In case of a sensing fiber in a metal tube, there is typically no need to consider pressure effects.

(2) Utilizing a hybrid Rayleigh/Brillouin technology developed by Kishida et al. (2014) to separate temperature and strain in same sensing fiber. This method is generally able to keep the same spatial resolution for temperature and strain, but the precision is limited by Brillouin. The recently developed Phase-Shift Pulse Brillouin Optical Time-Domain Reflectometry (PSP-BOTDR) can provide enough resolution and precision. See Shibata et al. (2017) and Nishiguchi et al. (2014).

(3) Utilizing a spatially designed cable that utilizes different sensing fibers to separate strain, pressure and temperature.

FIG. 2 shows an illustrative method 100 of determining borehole characteristics. The method 100 includes arranging at least one sensing fiber along a borehole, causing pressure changes in the borehole, and measuring strain along the sensing fiber to obtain strain data. In illustrative embodiments, the borehole along which the sensing fiber is arranged has been fractured (e.g., but not limited to, a naturally fractured borehole or a hydraulically fractured borehole). In illustrative embodiments, the borehole along which the sensing fiber is arranged is of a vertical producer well or of a vertical injector well. In illustrative embodiments, the borehole along which the sensing fiber is arranged is of a conventional well.

An illustrative method 100 can be performed using a DPATS (distributed pressure acoustic, temperature and strain) monitoring system such as that disclosed in U.S. Pat. No. 9,829,352, incorporated herein by reference in its entirety.

In illustrative methods, pressure changes in the borehole can be caused by shutting-in the borehole, changing a choke size of the borehole, and/or performing an injection in the borehole.

In illustrative methods, the measuring of strain along the sensing fiber is performed before the pressure changes to obtain a baseline strain reading, during pressure changes to obtain time-dependent strain variation data, and after the pressure changes to obtain strain recovery data. The strain data include the baseline strain reading, the time-dependent strain variation data, and the strain recovery data. In illustrative methods, the sensing fiber is an optic fiber.

In illustrative methods, the measuring of strain along the sensing fiber includes performing distributed strain sensing.

An illustrative method of determining borehole characteristics further comprises determining borehole fracture geometry based on the strain data.

An illustrative method of determining borehole characteristics further comprises determining borehole perforation efficiency based on the strain data.

An illustrative method of determining borehole characteristics further comprises measuring temperature along the sensing fiber to obtain temperature data.

An illustrative method of determining borehole characteristics further comprises obtaining pressure data from the borehole, and comparing the pressure data to the strain data to obtain cluster performance data.

FIG. 3 shows the steps of an illustrative well operation and data acquisition sequence to diagnose near-wellbore fracture and perforation efficiency. At step 1, a wellbore reaches stable production status, during which distributed strain sensing (DSS) monitoring is OFF. At step 2, stable production continues for a predetermined amount of time (e.g., but not limited to, 1-6 hours), during which DSS monitoring is turned ON to obtain a baseline strain measurement. At step 3, the wellbore is shut-in for a predetermined amount of time, during which DSS monitoring is ON to obtain time-dependent strain variation data. At step 4, the well is reopened to resume stable production status, during which DSS monitoring is ON to obtain strain recovery data. At step 5, production continues, and DSS monitoring is turned OFF at the completion of data acquisition.

Examples of strain data are graphed in FIGS. 4 and 5.

FIG. 4 shows an example of real field DSS measurement of strain variation due to a shut-in operation on a hydraulic-fractured oil producer. The temperature effects are eliminated utilizing DTSS in this case. The well was in production for more than a year after the hydraulic fracturing operation. A well operation and DSS data acquisition similar to that set forth in FIG. 3 were performed. The strain variation shown in FIG. 4 is the strain difference between 70 hours after the shut-in (step 3) and the stable flow period (step 2). Positive strain measurements can indicate the existence of near-wellbore fractures, which collocated with perforation clusters. The width of the positive region can be related to the fracture zone geometry, and the height and area can be linked to the amount of fracture width increase.

FIG. 5 shows an example of the difference of magnitude of positive strain observed at each perforation cluster location of an unconventional well with two different hydraulic fracturing designs. It can be observed that the difference of strain variation at various perforation cluster locations of each design is statistically significant, which illustrates the impact of hydraulic fracturing designs on the near-wellbore fractures.

Illustrative methods of the present disclosure can have various advantageous effects. Illustrative methods disclosed herein can result in high-quality strain distribution results, and effective near-wellbore strain measurements. Illustrative methods disclosed herein can provide desirable spatial resolution and high precision, so as to obtain useful information indicative of perforation cluster performance. Illustrative methods disclosed herein can provide non-intrusive processes which are easily applicable to wells equipped with a sensing fiber indicative of wellbore deformation. Illustrative methods disclosed herein can estimate near-wellbore fracture geometry and properties from measured strain signal by analyzing the shape and magnitude of the strain response, as well as the temporal relation between the strain signal and borehole pressure changes. Illustrative methods disclosed herein can help compare different hydraulic fracturing designs, which may impact near-wellbore hydraulic fracture geometries and which can greatly affect production performance of the well (see Lecampion et al. 2015). Illustrative methods disclosed herein can help estimate perforation efficiency from the strain variation measurements.

Moreover, for perforations or perforation clusters that are not producing due to proppant screen out or other reasons, little strain variation can be observed by the fiber near the perforation because the connection between the borehole and reservoir is likely lost. By examining the magnitude of strain variation at each perforation location, perforation efficiency can be estimated more effectively using illustrative methods disclosed herein. Furthermore, in accordance with illustrative methods disclosed herein, strain distribution of clusters can be monitored without needing additional well operation—the production-induced pressure depletion can instead be associated with long-term borehole strain changes. The measurement of strain can be arranged during the production life of the well, independently of other scheduled events.

It will be appreciated by those skilled in the art that the disclosure herein can be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The presently-disclosed embodiments are therefore considered in all respects to be illustrative and not restricted. The scope of the invention is indicated by the appended claims rather than the foregoing description and all changes that come within the meaning and range and equivalence thereof are intended to be embraced therein. The in-well pressure can be observed by separate pressure and temperature sensors. If distributed an optical sensing cable is used, the pressure and deformation relationship can be better established even in distributed level.

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Claims

1. A method of determining borehole characteristics comprising:

arranging at least one sensing fiber along a borehole;

causing pressure changes in the borehole; and

measuring strain along the at least one sensing fiber to obtain strain data.

2. The method of claim 1, wherein the borehole along which the at least one sensing fiber is arranged has been fractured.

3. The method of claim 2, further comprising:

determining borehole fracture geometry based on the strain data.

4. The method of claim 2, wherein the borehole along which the at least one sensing fiber is arranged has been hydraulically fractured.

5. The method of claim 2, wherein the borehole along which the at least one sensing fiber is arranged has been naturally fractured.

6. The method of claim 1, wherein the borehole along which the at least one sensing fiber is arranged is a borehole of a vertical producer well or of a vertical injector well.

7. The method of claim 1, wherein the borehole along which the at least one sensing fiber is arranged is a borehole of a conventional well.

8. The method of claim 1, further comprising:

determining borehole perforation cluster efficiency based on the strain data.

9. The method of claim 1, wherein the at least one sensing fiber includes at least one optic fiber.

10. The method of claim 1, wherein the causing of the pressure changes in the borehole includes at least one selected from the group consisting of: shutting-in the borehole, changing a choke size of the borehole, or performing an injection in the borehole.

11. The method of claim 1, wherein the measuring of strain along the at least one sensing fiber is performed before the pressure changes to obtain a baseline strain reading, during pressure changes to obtain time-dependent strain variation data, and after the pressure changes to obtain strain recovery data, wherein the strain data includes the baseline strain reading, the time-dependent strain variation data, and the strain recovery data.

12. The method of claim 1, wherein the measuring of strain along the at least one sensing fiber includes performing distributed strain sensing.

13. The method of claim 1, further comprising:

measuring temperature along the at least one sensing fiber to obtain temperature data.

14. The method of claim 1, further comprising:

obtaining pressure data from the borehole; and

comparing the pressure data to the strain data to obtain cluster performance data.

15. The method of claim 1, wherein the borehole is a borehole of a well undergoing production, and the method further comprises:

ceasing production from the well prior to the causing of the pressure changes in the borehole; and

resuming production from the well after the causing of the pressure changes in the borehole.