SYSTEM AND METHOD FOR NUMERICAL SIMULATION FOR FRACTURE DRIVEN INTERACTION

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not applicable.

TECHNICAL FIELD

The disclosed embodiments relate generally to techniques related to fracture driven interaction simulation.

BACKGROUND

Fracture Driven Interactions (FDIs) are the phenomena where child well hydraulic fractures preferentially propagate towards nearby depleted nearby parent wells. This phenomenon has attracted much attention in the industry since it can lead to a few consequences. To mitigate FDI, several methods have been trialed in various plays. A need continues to exist in the area of fracture drive interaction simulation.

SUMMARY

In accordance with some embodiments, a method of calculating Water Movement from Child well to Parent well is disclosed. The method may include obtaining hydraulic fracturing data for a subsurface volume of interest. The subsurface volume of interest comprises at least one parent well drilled into the subsurface volume of interest, at least one parent well hydraulic fracture, at least one child well drilled into the subsurface volume of interest, and at least one child well hydraulic fracture. The method may include constructing a structured grid model using the obtained hydraulic fracturing data. The structured grid model includes time-varying connectivity equivalent to the at least one parent well hydraulic fracture and the at least one child well hydraulic fracture to represent dynamically changing connectivity between wells and capture hydraulic fracturing growth. The method may include embedding fracture flow-based parameters into the structured grid model to generate a fine scale grid of permeability values. The method may include upscaling the fine scale grid of permeability values into a coarse scale grid of permeability values to determine a single connectivity value for each well pair. The method may include constructing a time varying connectivity curve for each well pair using the determined connectivity values for each well pair. The method may include utilizing the time varying connectivity curve to calculate the Water Movement from Child well to Parent well.

In yet another aspect of the present invention, to address the aforementioned problems, some embodiments provide a computer system. The computer system includes one or more processors, memory, and one or more programs. The one or more programs are stored in memory and configured to be executed by the one or more processors. The one or more programs include an operating system and instructions that when executed by the one or more processors cause the computer system to perform any of the methods provided herein. The method may include obtaining hydraulic fracturing data for a subsurface volume of interest. The subsurface volume of interest comprises at least one parent well drilled into the subsurface volume of interest, at least one parent well hydraulic fracture, at least one child well drilled into the subsurface volume of interest, and at least one child well hydraulic fracture. The method may include constructing a structured grid model using the obtained hydraulic fracturing data. The structured grid model includes time-varying connectivity equivalent to the at least one parent well hydraulic fracture and the at least one child well hydraulic fracture to represent dynamically changing connectivity between wells and capture hydraulic fracturing growth. The method may include embedding fracture flow-based parameters into the structured grid model to generate a fine scale grid of permeability values. The method may include upscaling the fine scale grid of permeability values into a coarse scale grid of permeability values to determine a single connectivity value for each well pair. The method may include constructing a time varying connectivity curve for each well pair using the determined connectivity values for each well pair. The method may include utilizing the time varying connectivity curve to calculate the Water Movement from Child well to Parent well.

In another aspect of the present invention, to address the aforementioned problems, some embodiments provide a non-transitory computer readable storage medium storing one or more programs. The one or more programs comprise instructions, which when executed by a computer system with one or more processors and memory, cause the computer system to perform any of the methods provided herein. The method may include obtaining hydraulic fracturing data for a subsurface volume of interest. The subsurface volume of interest comprises at least one parent well drilled into the subsurface volume of interest, at least one parent well hydraulic fracture, at least one child well drilled into the subsurface volume of interest, and at least one child well hydraulic fracture. The method may include constructing a structured grid model using the obtained hydraulic fracturing data. The structured grid model includes time-varying connectivity equivalent to the at least one parent well hydraulic fracture and the at least one child well hydraulic fracture to represent dynamically changing connectivity between wells and capture hydraulic fracturing growth. The method may include embedding fracture flow-based parameters into the structured grid model to generate a fine scale grid of permeability values. The method may include upscaling the fine scale grid of permeability values into a coarse scale grid of permeability values to determine a single connectivity value for each well pair. The method may include constructing a time varying connectivity curve for each well pair using the determined connectivity values for each well pair. The method may include utilizing the time varying connectivity curve to calculate the Water Movement from Child well to Parent well.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A illustrates an example system of calculating Water Movement from Child well to Parent well (WMCP), which is referred to as a WMCP system herein. FIG. 1B illustrates an example method of calculating Water Movement from Child well to Parent well (WMCP), which is referred to as a WMCP process herein. FIG. 1C illustrates the detailed steps of FDI process.

FIG. 2 illustrates time-varying transmissibility to represent growing hydraulic fractures.

FIG. 3 illustrates an example of constructed transmissibility growth rate as increasing fluid intensity at different well spacing.

FIG. 4 illustrates fracture flow-based upscaling to compute connectivity.

FIG. 5 illustrates a process to compute a transmissibility representing connectivity between wells.

FIG. 6 illustrates a defined drainage region (left) and one cross section view (right).

FIG. 7 illustrates a dynamic change of water volume in Parent drainage area due to Child hydraulic fracturing.

FIG. 8 illustrates field data-sharp increased water production in Parent-1 as result of Child hydraulic fracturing.

FIG. 9 illustrates an example of correlation between Estimated Ultimate Recovery (EUR)/ft and fluid intensity.

FIG. 10A illustrates a field application that includes 4 wells-two parent wells and two child wells. FIG. 10B illustrates historical and (history matched) simulation Parent wells' liquid production rate (top) and water production rate (bottom).

FIG. 11 illustrates sensitivity parameter-well spacing scenarios.

FIG. 12 illustrates computed well connectivity (Parent-Child) for each scenario.

FIGS. 13A-13B illustrates sensitivity of well spacing and depletion to a volume of Water Movement from Child well to Parent well (WMCP).

FIG. 14 illustrates a Table 1, which is a depletion table illustrating Child EUR loss constructed based on the WMCP process provided herein. Here, Spacing C>Spacing B>Spacing A and Depletion 4>Depletion 1.

Like reference numerals refer to corresponding parts throughout the drawings.

DETAILED DESCRIPTION OF EMBODIMENTS

Fracture Driven Interactions (FDIs) are the phenomena where child well hydraulic fractures preferentially propagate towards nearby depleted parent wells. This phenomenon has attracted much attention in the industry since it can lead to a few consequences. Based on extensive reviews of FDIs in S&T plays, the majority of FDIs present the following three observations:

- 1. Parent well pressure increase. During the stimulation of a child well (or simply child herein), pressure in the parent well (or simply parent herein) can increase from several psi to several thousand psi. The value and speed of pressure increase vary from case to case. This pressure increase can lead to facility damage to the parent well, as well as sand mobilization affecting production.
- 2. Parent well water production increase. Often the water-cut in the parent well increases significantly, sometimes to pure water production for several months. In most cases, the oil production can recover after extensive time. However, the water production is still a loss due to the missed opportunity of producing oil. This is called Loss of Production Opportunities (LPO). In some cases, the production in the parent well can increase for a short period of time. This phenomenon is more often observed in one basin where parent well completion was relatively small.
- 3. Child well production loss. The performance of child wells can be noticeably lower than parent wells. The level of underperformance can be as much as 30-50% according to reviews.

Many researchers have done extensive work to understand the root cause of FDI. Based on the level of pressure increase amount and speed, the type of FDI is categorized into: undrained poro-elastic (stress shadowing), indirect FDI (fluid migration), and direct FDI. Since direct communication is much more impactful than others in terms of EUR and LPO, this disclosure will focus on the scenarios of direct communication between parent and child wells.

To mitigate FDI, several methods have been trialed in various plays. Pre-loading the parent well was a popular mitigation method. This method uses water or another type of fluid to inject into the depleted parent well to increase the pressure. Field trials show that pre-loading has limited impacts due to the limited volume that is injected into the parent well. Other efforts include diverter, which also generated mixed results.

In short, Fracture Driven Interaction (FDI) is the phenomenon due to the depletion effects from parent wells affecting the fracture growth from child wells during the stimulation process. The child well hydraulic fractures preferentially propagate towards the lower pressured depleted regions. As a result of FDI, parent wells often experience high water cut after the event, causing Lost Production Opportunities (LPO). In addition, FDI-related water movement leads to ineffective stimulation of the child well, which often results in lower-than-expected Estimated Ultimate Recovery (EUR).

Described below are methods, systems, and computer-readable storage media that calculate Water Movement from Child well to Parent well. In accordance with some embodiments, a method of calculating Water Movement from Child well to Parent well is disclosed. The method may include obtaining hydraulic fracturing data for a subsurface volume of interest. The subsurface volume of interest comprises at least one parent well drilled into the subsurface volume of interest, at least one parent well hydraulic fracture, at least one child well drilled into the subsurface volume of interest, and at least one child well hydraulic fracture. The method may include constructing a structured grid model using the obtained hydraulic fracturing data. The structured grid model includes time-varying connectivity equivalent to at least one parent well hydraulic fracture and at least one child well hydraulic fracture to represent dynamically changing connectivity between wells and capture hydraulic fracturing growth. The method may include embedding fracture flow-based parameters into the structured grid model to generate a fine scale grid of permeability values. The method may include upscaling the fine scale grid of permeability values into a coarse scale grid of permeability values to determine a single connectivity value for each well pair. The method may include constructing a time-varying connectivity curve for each well pair using the determined connectivity values for each well pair. The method may include utilizing the time-varying connectivity curve to calculate the Water Movement from Child well to Parent well.

In this disclosure, the focus is on the main mechanism of FDI. Albeit multiple factors contribute to this FDI process, a WMCP methodology (e.g., WMCP methodology embodiment referred to as WMCP process 50) provided herein determines a variable (referred to as WMCP) that can reflect major contributing parameters (e.g., geology, completion design, depletion status of parent well) and be indicative of parent well LPO and child well EUR loss. This WMCP variable may be used to seek alternative completion designs that would reduce the impact of FDI. Furthermore, this WMCP variable may be used to develop a quantitative tool that can provide estimates of economic impacts as a function of design parameters that can be controlled (e.g., well spacing, well landing, and parent well depletion time).

As explained herein, this WMCP methodology may be a reliable numerical tool to forecast and eventually minimize FDI impacts. Furthermore, in traditional numerical workflows, the fracture propagation simulation is often not fully coupled with fluid flow into depleted reservoirs or pre-existing hydraulic fractures. Therefore, these workflows have challenges in forecasting the LPO from parent wells and EUR loss from child wells when a full field well model is considered. Even with newly developed numerical simulation engines, improvements are desirable. The WMCP methodology provided herein addresses this challenge. For instance, in the WMCP methodology provided herein, the simulation may be performed in two steps: 1. calculate the connectivity between the parent and child well during the child hydraulic fracture propagation process. 2. utilize the time-varying connectivity curve to calculate the amount of water invasion into the parent well region during child well hydraulic fracturing. The LPO and EUR can be calculated either using production forecasts from a flow simulator following the water invasion process or by correlation using frac fluid intensity and EUR from data analytics.

The WMCP methodology provided herein has been evaluated in multiple models, including conceptual models and a field case. This disclosure demonstrates how this WMCP methodology can effectively calculate the water cut increase in the parent well following the FDI. In addition, scaling of the solution as well as the approach to real-world cases that need to consider multiple wells in multiple benches are discussed herein. Sensitivity cases like well spacing and parent well depletion level's impact were also analyzed using this numerical methodology provided herein. More importantly, observations and analysis based on this WMCP methodology and its application to a field model will be demonstrated, which helped to establish best practices and guidelines to be used in forecasting the LPO from parent wells and EUR loss from child wells.

Advantageously, embodiments consistent with this disclosure may be used for FDI numerical simulation. The WMCP methodology provided herein bypassed the challenge of explicitly simulating water flow during hydraulic fracture propagation, which is extremely hard to constrain. This WMCP methodology provided herein has the potential to be applied to other scenarios where fluid flow and cross-well connectivity are important.

Advantageously, the power and utility of the WMCP methodology provided herein may be presented, as to its computational efficiency while accuracy and quality results with regard to the estimation of LPO and EUR, are demonstrated through field application. The integration of this WMCP methodology into shale and tight phased development optimization processes may be useful to achieve improved (e.g., optimum) well spacing and timing of child well development to maximize recovery.

Advantageously, embodiments consistent with this disclosure may be utilized for implementing or adjusting, based on the output (e.g., computer output), a design parameter for a wellbore of the subsurface volume of interest. Advantageously, embodiments consistent with this disclosure may be utilized for implementing or adjusting, based on the output (e.g., computer output), an operating parameter for a wellbore of the subsurface volume of interest. The wellbore may be a parent wellbore in some embodiments. The wellbore may be a child wellbore in some embodiments. The wellbore may be a new wellbore in some embodiments. The wellbore may be an existing wellbore in some embodiments. Some non-limiting examples of design parameters include, but are not limited to, stage size, cluster spacing, fluid intensity, etc. Some non-limiting examples of operating parameters include, but are not limited to, bottom hole pressures, flow rate constraints, etc.

Reference will now be made in detail to various embodiments, examples of which are illustrated in the accompanying drawings. In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the present disclosure and the embodiments described herein. However, embodiments described herein may be practiced without these specific details. In other instances, well-known methods, procedures, components, and mechanical apparatus have not been described in detail so as not to unnecessarily obscure aspects of the embodiments.

The methods and systems of the present disclosure may be implemented by a system and/or in a system, such as a system 10, such as a WMCP system, shown in FIG. 1A. The system 10 may include one or more of a processor 11, an interface 12 (e.g., bus, wireless interface), an electronic storage 13, a graphical display 14, and/or other components. The processor 11 may perform a method of calculating Water Movement from Child well to Parent well.

The electronic storage 13 may be configured to include any electronic storage medium that electronically stores information. The electronic storage 13 may store software algorithms, information determined by the processor 11, information received remotely, and/or other information that enables the system 10 to function properly. For example, the electronic storage 13 may store information relating to input such as geologic grid properties, reservoir properties, completion parameters, completion pumping schedule, production history, pressure readings, reservoir model in coarse scale, other input, and/or other information. For example, the electronic storage 13 may store information relating to output such as simulated production history, water saturation changes in the grid cells, WMCP, EUR, LPO, other output, and/or other information. The electronic storage media of the electronic storage 13 may be provided integrally (i.e., substantially non-removable) with one or more components of the system 10 and/or as removable storage that is connectable to one or more components of the system 10 via, for example, a port (e.g., a USB port, a Firewire port, etc.) or a drive (e.g., a disk drive, etc.). The electronic storage 13 may include one or more of optically readable storage media (e.g., optical disks, etc.), magnetically readable storage media (e.g., magnetic tape, magnetic hard drive, floppy drive, etc.), electrical charge-based storage media (e.g., EPROM, EEPROM, RAM, etc.), solid-state storage media (e.g., flash drive, etc.), and/or other electronically readable storage media. The electronic storage 13 may include one or more non-transitory computer readable storage medium storing one or more programs. The electronic storage 13 may be a separate component within the system 10, or the electronic storage 13 may be provided integrally with one or more other components of the system 10 (e.g., the processor 11). Although the electronic storage 13 is shown in FIG. 1 as a single entity, this is for illustrative purposes only. In some implementations, the electronic storage 13 may comprise a plurality of storage units. These storage units may be physically located within the same device, or the electronic storage 13 may represent storage functionality of a plurality of devices operating in coordination.

The graphical display 14 may refer to an electronic device that provides visual presentation of information. The graphical display 14 may include a color display and/or a non-color display. The graphical display 14 may be configured to visually present information. The graphical display 14 may present information using/within one or more graphical user interfaces. For example, the graphical display 14 may present information relating to simulated production history, water saturation changes in the grid cells, simulated pressure field, water/oil/gas saturation in each grid cell, permeability field, WMCP, EUR, LPO, intermediate & final results, and/or other information.

The processor 11 may be configured to provide information processing capabilities in the system 10. As such, the processor 11 may comprise one or more of a digital processor, an analog processor, a digital circuit designed to process information, a central processing unit, a graphics processing unit, a microcontroller, an analog circuit designed to process information, a state machine, and/or other mechanisms for electronically processing information. The processor 11 may be configured to execute one or more machine-readable instructions 100 to facilitate Water Movement from Child well to Parent well (WMCP) calculation. The machine-readable instructions 100 may include one or more computer program components. The machine-readable instructions 100 may include a hydraulic fracturing data component 102, a structured grid model component 104, a fine scale grid component 106, a coarse scale grid component 108, a time varying connectivity curve component 110, a Water Movement from Child well to Parent well (WMCP) component 112, loss of production (LPO) component 114, estimated ultimate recovery (EUR) component 116 and/or other computer program components.

It should be appreciated that although computer program components are illustrated in FIG. 1A as being co-located within a single processing unit, one or more of computer program components may be located remotely from the other computer program components. While computer program components are described as performing or being configured to perform operations, computer program components may comprise instructions which may program processor 11 and/or system 10 to perform the operation.

While computer program components are described herein as being implemented via processor 11 through machine-readable instructions 100, this is merely for ease of reference and is not meant to be limiting. In some implementations, one or more functions of computer program components described herein may be implemented via hardware (e.g., dedicated chip, field-programmable gate array) rather than software. One or more functions of computer program components described herein may be software-implemented, hardware-implemented, or software and hardware-implemented.

Referring again to machine-readable instructions 100, the hydraulic fracturing data component 102 may be configured to obtain hydraulic fracturing data for a subsurface volume of interest. The subsurface volume of interest comprises at least one parent well drilled into the subsurface volume of interest, at least one parent well hydraulic fracture, at least one child well drilled into the subsurface volume of interest, and at least one child well hydraulic fracture.

The structured grid model component 104 may be configured to construct a structured grid model using the obtained hydraulic fracturing data. The structured grid model includes time-varying connectivity equivalent to the at least one parent well hydraulic fracture and the at least one child well hydraulic fracture to represent dynamically changing connectivity between wells and capture hydraulic fracturing growth.

The fine scale grid component 106 may be configured to embed fracture flow-based parameters into the structured grid model to generate a fine scale grid of permeability values.

The coarse scale grid component 108 may be configured to upscale the fine scale grid of permeability values into a coarse scale grid of permeability values to determine a single connectivity value for each well pair.

The time varying connectivity curve component 110 may be configured to construct a time varying connectivity curve for each well pair using the determined connectivity values for each well pair.

The Water Movement from Child well to Parent well (WMCP) component 112 may be configured to utilize the time varying connectivity curve to calculate the Water Movement from Child well to Parent well. Component 112 as well as other components may utilize a simulator, such as a reservoir simulator.

The loss of production (LPO) component 114 may be configured to determine loss of production using the calculated Water Movement from Child well to Parent well for the at least one parent well.

The estimated ultimate recovery (EUR) component 116 may be configured to determine estimated ultimate recovery using the calculated Water Movement from Child well to Parent well for the at least one child well.

The description of the functionality provided by the different computer program components described herein is for illustrative purposes, and is not intended to be limiting, as any of computer program components may provide more or less functionality than is described. For example, one or more of computer program components may be eliminated, and some or all of its functionality may be provided by other computer program components. As another example, processor 11 may be configured to execute one or more additional computer program components that may perform some or all of the functionality attributed to one or more of computer program components described herein.

FIG. 1B illustrates an example WMCP process 50 of calculating Water Movement from Child well to Parent well. Hydraulic fracturing is a crucial technique for enhancing reservoir productivity, particularly in unconventional formations such as shale and tight rocks. The process 50 describes the approach to use to represent the hydraulic fracturing growth process, calculate WMCP within the simulation model, and use it as proxy for child well EUR loss.

At step 55, the WMCP process 50 includes obtaining hydraulic fracturing data for a subsurface volume of interest. The subsurface volume of interest includes at least one parent well drilled into the subsurface volume of interest, at least one parent well hydraulic fracture, at least one child well drilled into the subsurface volume of interest, and at least one child well hydraulic fracture. The hydraulic fracturing data may include geometry of a hydraulic fracture, permeability of a hydraulic fracture, porosity of a hydraulic fracture, other property geometry of a hydraulic fracture, conductivity of a hydraulic fracture, or any combination thereof. A parent well hydraulic fracture is a hydraulic fracture corresponding to a parent well. A child well hydraulic fracture is a hydraulic fracture corresponding to a child well. At least one parent well hydraulic fracture and one least one child well hydraulic fracture may interact, and thus, there may be a connection between at least one parent well and at least one child well.

At step 60, the WMCP process 50 includes constructing a structured grid model using the obtained hydraulic fracturing data, wherein the structured grid model includes time-varying connectivity equivalent to the at least one parent well hydraulic fracture and the at least one child well hydraulic fracture to represent dynamically changing connectivity between wells and capture hydraulic fracturing growth. The step 60 may include constructing a structured grid model with time varying transmissibility as depicted in FIG. 2. This grid facilitates the easy capture of where injected pumping fluid is dispersed and how fast the fluid moves toward other wells within the simulation model. The hydraulic fracturing data for the subsurface volume of interest may be utilized at the step 60. The subsurface volume of interest includes at least one parent well drilled into the subsurface volume of interest, at least one parent well hydraulic fracture, at least one child well drilled into the subsurface volume of interest, and at least one child well hydraulic fracture.

This approach offers several advantages, including easier scalability to large-scale problems (involving multiple wells and benches). Typically, it achieves this through computational efficiency in building models, especially when compared to other gridding technologies like embedded discrete fracture and unstructured grid.

At step 65, the WMCP process 50 includes embedding fracture flow-based parameters into the structured grid model to generate a fine scale grid of permeability values. The process to compute the connectivity or transmissibility is based on the fracture flow-based upscaling technique in Oda, M. (1985) ‘Permeability tensor for discontinuous rock masses’, Geo technique. ICE Publishing, 35 (4), pp. 483-495.

Doi: 10.1680/geot.1985.35.4.483, which is incorporated by reference. To illustrate the process, three different fracture models are introduced, which were obtained at different pumping volumes injected as shown in FIG. 4. ‘P’ in the figure denotes Parent well while ‘C’ represents Child well. Each of the fracture models in the first row is upscaled to structured grids, which are shown in the second and third rows. Larger hydraulic fracture models, when more pumping fluid is injected, create more enhanced permeability resulting in higher connectivity between wells.

At step 70, the WMCP process 50 includes upscaling the fine scale grid of permeability values into a coarse scale grid of permeability values to determine a single connectivity value for each well pair (e.g., parent-parent, parent-child, and child-child). To compute a representative connectivity between wells, another coarsening step is followed with upscaling fine grid cells to a coarse cell as described in FIG. 5. For each coarse scale block, solve the single-phase pressure equation over the local region to compute K*. Once K* is computed, the computed coarse scale perm (K*_coarse) is divided by K_original(perm before hydraulic fracturing) to compute the Permeability Multiplier (equivalently Transmissibility Multiplier). As a result of constructing the connectivity library, it enables the efficient application of the transmissibility multiplier at different time steps in the simulation model to closely represent the growth of a hydraulic fracture.

At step 75, the WMCP process 50 includes constructing a time-varying connectivity curve for each well pair. Surveillance techniques like microseismic and fiber optic sensing provide valuable insights into the extent and growth rate of hydraulic fractures. However, forecasting fracture fluid movement along with hydraulic fractures remains challenging under varying conditions, including different formations, pumping volumes, and completion designs, etc. To address this challenge, a commercial hydraulic fracture simulator was utilized for predictive modeling, combined with a flow simulator to capture dynamically varying connectivity between wells, and ultimately estimate fracture fluid movement contrasts in different subsurface conditions and completion designs. Subsequently, the fracture model is upscaled to a structured grid, representing fractures with enhanced permeability or transmissibility. Testing it under thousands of varying conditions allows us to build a valuable library of knowledge ready to be applied. FIG. 3 shows an example of a connectivity library, which estimates connectivity at different well spacing scenarios (660 ft, 880 ft, 1000 ft) with varying pumping fluid volume injected. As expected, there is higher connectivity between wells when more pumping fluid is injected. Also, there is higher connectivity at smaller well spacing than larger well spacing cases. These findings align with observations made by other researchers. Abivin, Patrice, et al. “Data Analytics Approach to Frac Hit Characterization in Unconventional Plays: Application to Williston Basin.” Paper presented at the International Petroleum Technology Conference, Dhahran, Kingdom of Saudi Arabia, January 2020. Doi: https://doi.org/10.2523/IPTC-20162-MS, which is incorporated by reference, concluded that the median normalized production of child wells is, on average, 20-45% lower than that of their nearest parent well. Furthermore, the disparity between parent and child well production increases as the spacing tightens. In a separate study, Niederhut, Dillon, et al. “Understanding the Drivers of Parent-Child Depletion: A Machine Learning Approach.” Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, Denver, Colorado, USA, June 2023. Doi:

https://doi.org/10.15530/urtec-2023-3862321, which is incorporated by reference, found that the effect of distance between parent wells and infill wells is non-linear and concave downward. The inflection point, at which interwell distance significantly impacts child well performance, appears to occur around 1,000 feet.

At step 80, the WMCP process 50 includes utilizing the time-varying connectivity curve to calculate the Water Movement from Child well to Parent well (e.g., a volume of water movement from child well to parent well during child well hydraulic fracturing). In addition to the capability to model the growth of hydraulic fractures in the simulation model, tracing injection fluid is also enabled in this WMCP process 50. This feature allows monitoring of the movement and behavior of the injected fluid during the hydraulic fracturing process. As discussed herein, based on internal field data analysis, although the exact relationship remains undiscovered, it is tentatively concluded that EUR loss from the child well is most strongly associated with the volume of water movement from Child to Parent (WMCP) during hydraulic fracturing of the Child well (called after, WMCP@FDI).

To estimate the WMCP, as depicted in FIG. 6, a numerical flow simulation model is used, which enables dynamically tracking the water volume moved from the Child to Parent drainage region that is typically defined with a radius from the Parent well. The increased water volume in each Parent drainage area is an important indicator for explaining Child fracture fluid loss, which ultimately leads to a reduction in the stimulated area.

As illustrated in FIG. 7, the increased water volume in the Parent well contributes to increased water production or water cut of the Parent well. The additional water production from the Parent well is directly proportional to the WMCP. Following FIG. 8, based on one of field data, illustrates increased water production from Parent 1 as a result of Child hydraulic fracturing. In contrast, the water production volume from Parent 2 (located farther from the Child well) remains relatively unaffected.

More specifically, the numerical simulator may be utilized to calculate WMCP. In the numerical simulator, the user inputs the pump schedule of the child well. Using the time-varying connectivity, the numerical simulator does the calculation (e.g., using material balance, Darcy's law, and other numerical models) to calculate the water volume increase in the cells around the parent well. The added water volume due to child well injection will be the WMCP.

WMCP may be calculated for each well pair or as a whole. If there are only two wells, then it is more straightforward: the WMCP=volume of water increase in parent=volume of water loss from child. If there are multiple well pairs, then WMCP=total parent well water volume increase=total child well water loss. The closer child well will lose more water and the closer parent well likely will get more water. These can all be calculated using the reservoir simulator. In some embodiments, it makes more sense to calculate a total WMCP for parent and child wells.

At step 85, the process 50 includes determining the loss of production (LPO) using the calculated Water Movement from Child well to Parent well for at least one parent well. As illustrated in FIG. 7, the increased water volume in the Parent well contributes to increased water production or water cut of the Parent well. The additional water production from the Parent well is directly proportional to the WMCP. Following FIG. 8, based on one of field data, illustrates increased water production from Parent 1 as a result of Child hydraulic fracturing. In contrast, the water production volume from Parent 2 (located farther from the Child well) remains relatively unaffected.

More specifically, the LPO may be determined using the WMCP by using the linear correlation between fluid intensity and EUR, as illustrated in FIG. 9. If WMCP is 500, as an example, then it can be assumed that the 500 units of water which should have created new fracture(s), now flow to the parent well. As a result of that, the fluid intensity decreased by 500 units. Using the linear correlation in FIG. 9, the EUR would have been reduced by the corresponding amount.

At step 90, the WMCP process 50 includes determining estimated ultimate recovery (EUR) using the calculated Water Movement from Child well to Parent well for at least one child well. The Child well experiences a loss of hydraulic fracturing fluid, which should ideally contribute to creating its own stimulated volume. If the loss of Child fracture fluid is related to EUR loss based on the field data example shown in FIG. 9, then the step 90 is able to estimate possible EUR loss in the Child well as a result of reduced stimulated volume caused by the loss of fracturing fluid. The exact relationship between the loss volume of fracture fluid and EUR remains to be further discovered through extensive studies. In this approach, WMCP (estimated from the simulation model) is utilized as Child fracture fluid loss volume. Then, the step 90 incorporates relevant area data, considering the correlation between EUR/ft and fluid intensity, to estimate the potential EUR loss of the Child well. This approach has proven to be computationally efficient as it utilizes a faster modeling method as well as leverages a built-in library (if necessary) to forecast the impact of FDI. Additionally, this approach has generated predictions that are comparable to historical performances, of which a field example is discussed herein.

At step 91, the WMCP process 50 includes utilizing the calculated Water Movement from Child well to Parent well for implementing or adjusting a design parameter for a well of the subsurface volume of interest. At step 92, the WMCP process 50 includes utilizing the calculated Water Movement from Child well to Parent well for implementing or adjusting an operating parameter for a well of the subsurface volume of interest. Indeed, the calculated Water Movement from Child well to Parent well is utilized for implementing or adjusting a design parameter for a well of the subsurface volume of interest and/or utilized for implementing or adjusting an operating parameter for a well of the subsurface volume of interest. The wellbore may be a parent wellbore in some embodiments. The wellbore may be a child wellbore in some embodiments. The wellbore may be a new wellbore in some embodiments. The wellbore may be an existing wellbore in some embodiments. Some non-limiting examples of design parameters include, but are not limited to, stage size, cluster spacing, fluid intensity, well spacing, etc. Some non-limiting examples of operating parameters include, but are not limited to, bottom hole pressures, flow rate constraints, parent well depletion, etc. Implementing or adjusting a parameter (e.g., such as a design parameter, operating parameter, etc.) may reduce the impact of FDI.

Indeed, through observation of the detailed process of FDI, the following steps are involved in a FDI direct communication event (FIG. 1C): 1. Parent well is depleted around hydraulic fractures creating low pressure/stress zones. 2. Child well hydraulic fractures propagate around the perforations. 3. As Child well hydraulic fractures propagate in the depleted region, they start to grow preferentially towards the parent well depleted regions due to lower stress. Upon intersection, Child well hydraulic fractures start to connect with existing parent well hydraulic fractures. 4. Frac fluid from the Child well starts to flow into the Parent well hydraulic fracture. Due to the connection of the Parent wellbore, the frac fluid can flow into anywhere in the Parent well where pressure is low. 5. Child well hydraulic fractures stop growing due to frac fluid loss into Parent well hydraulic fractures. The Parent well pressure increases as the wellbore and surrounding reservoirs are loaded with frac fluid from the Child well.

The water loading in the Parent well will flush the oil from the wellbore away into neighboring wells so that the water cut increases dramatically after a direct communication FDI event. Since water preferentially flows into regions with high connectivity, for example, wellbore and proppant-filled hydraulic fractures, the Parent well will not be able to produce any hydrocarbon until this water is produced out from the parent well. Hence, the frac fluid that flowed into the Parent well depleted region is indicative of the LPO of the Parent well following the direct communication FDI event.

For the Child well, because the frac fluid flowed into the Parent well depleted region, new fracture surface areas are significantly reduced. Surface area is critical in providing production for the child well. If fracture surface area is significantly reduced, the EUR should also be significantly reduced. Assuming a relatively constant hydraulic fracture width, the fracture surface area lost is proportional to the volume of frac fluid that is lost into the parent well depleted regions.

From earlier analysis, it can be concluded that the key variable that connects parent well LPO and child well EUR is the amount of frac fluid that flowed from the Child well to the Parent well due to the depletion. Thus, the term Water Movement from Child to Parent (WMCP) has been provided herein. WMCP itself will depend on the level of depletion of the Parent well, completion design of parent and child wells, and many other factors. The process 50 provided a numerical workflow for calculating WMCP and used it as a proxy for Parent well LPO and Child well EUR. The strengths of the process 50 and WMCP have been highlighted herein, and a field case is provided herein below consistent with the process 50 to demonstrate the impacts of depletion and well spacing on FDI.

Field Application—An approach consistent with the process 50 to estimate the impact of FDI on Child well EUR is applied to a field case. In the field application, 4 wells were selected—two parent wells and two child wells as illustrated in FIG. 10A—to focus on identifying interaction between Parent and Child wells before and after child hydraulic fracturing. In the middle of each graph in FIG. 10B, there is a vertical bar indicating that a child well hydraulic fracturing event occurred. After the child well hydraulic fracturing, a sharp increase in water production from Parent-1 is observed due to the hydraulic fracturing impact. A flow simulation model is built in a structured grid. The connectivity between wells is calibrated in an attempt at history matching to match historical production rates (oil, gas, water) while bottom hole pressure is used as a constraint.

After history matching, the study is focused on estimating the sensitivity of well spacing and parent well depletion status to child well EUR predicted based on computed WMCPs. Essentially, the goal is to determine the optimum well spacing as well as the ideal parent depletion status which minimizes the impacts of FDI on child EUR. The team introduced smaller spacing and larger spacing in addition to base well spacing as shown in FIG. 11. For parent well depletion status, four different depletion scenarios are considered in FIG. 12. The computed connectivity between parent and child wells for each scenario confirms that larger well spacing results in lower connectivity while approximately 15% higher connectivity at shorter spacing than base well spacing at the same depletion status. Connectivity between wells is less sensitive to parent depletion status than well spacing. Depletion impacts vary within 10-15% depending on the chosen well spacing.

After the base study of connectivity, a total of 12 simulation models were set up, considering 3 well spacings across 4 depletion status. In the methodology provided herein, the focus was on estimating WMCP (Water Movement from Child to Parent) for each scenario and comparing it with the others, as illustrated in FIGS. 13A-13B. In FIG. 13A, the middle curve corresponds to Spacing B for each depletion, the top curve (above the middle curve) corresponds to Spacing A for each depletion, and the bottom curve (below the middle curve) corresponds to Spacing C for each depletion. In FIG. 13B, the middle column corresponds to Spacing B for each depletion, the first column (left of the middle column) corresponds to Spacing A for each depletion, and the third column (right of the middle column) corresponds to Spacing C for each depletion. In this field case, approximately a 5% increase in WMCP is observed when changing to shorter spacing from base spacing. Conversely, there is a 5% reduction in WMCP when changing to larger spacing from base spacing. In terms of depletion impact, greater depletion status results in generating larger WMCP in general. However, the magnitude of impact due to depletion is much smaller than that caused by well spacing.

The discounted Estimated Ultimate Recovery (EUR) was estimated by examining the correlation between fluid intensity and EUR (FIG. 9), which links the loss of hydraulic fracture fluid to WMCP. The calculations suggest that the impact of parent well depletion status on the child well's EUR discount is minor compared to the impact of well spacing. In this specific study area, adjusting the spacing from C to B or B to A results in an additional ˜5% EUR discount, regardless of the parent's depletion status. A 16% reduction estimate in EUR for a child well installed during the parent's Depletion 1 state, compared to an undisturbed well with the same spacing in the targeted development area. An example of the depletion table is shown in FIG. 14, which shows Child Well EUR loss as a function of depletion and well spacing.

Summary of Findings and Observations from the Study are as Follows:

Through analysis of field data of the FDI process, it was observed that the Estimated Ultimate Recovery (EUR) loss from the child well is most closely related to the Water Movement from Child to Parent (WMCP) during child well hydraulic fracturing.

The numerical simulation workflow has been tuned or modified to utilize time-varying transmissibility and define connectivity between wells within a structured simulation grid, which enables tracking frac-fluid and computing WMCP dynamically.

The WMCP process demonstrates both computational efficiency and effectiveness during simulation model building and history matching in a field application as it is a quicker method to build an effective simulation model utilizing a connectivity library defining the relationship between wells during and after hydraulic fracturing.

The impacts of well spacing and parent depletion on child EUR estimated from this WMCP methodology provide insights into FDI mitigation and optimum development strategy. For the particular study area, the parent depletion status impact on EUR discount is relatively small compared to the well spacing impact in general.

A more comprehensive study by integrating more subsurface uncertainties into this study is proposed to provide more reliable forecasting.

More information may be found in the following item: Park, Han Young, et al. “Numerical Simulation of FDI Impacts on Parent Well LPO and Child Well EUR in S&T.” URTEC-4044785-MS. Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, Houston, Texas, USA, June 2024.

doi: https://doi.org/10.15530/urtec-2024-4044785, which is incorporated by reference.

While particular embodiments are described above, it will be understood it is not intended to limit the invention to these particular embodiments. On the contrary, the invention includes alternatives, modifications, and equivalents that are within the spirit and scope of the appended claims. Numerous specific details are set forth in order to provide a thorough understanding of the subject matter presented herein. But it will be apparent to one of ordinary skill in the art that the subject matter may be practiced without these specific details. In other instances, well-known methods, procedures, components, and circuits have not been described in detail so as not to unnecessarily obscure aspects of the embodiments.

The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the description of the invention and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will also be understood that the term “and/or” as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items. It will be further understood that the terms “includes,” “including,” “comprises,” and/or “comprising,” when used in this specification, specify the presence of stated features, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, operations, elements, components, and/or groups thereof.

As used herein, the term “if” may be construed to mean “when” or “upon” or “in response to determining” or “in accordance with a determination” or “in response to detecting,” that a stated condition precedent is true, depending on the context. Similarly, the phrase “if it is determined [that a stated condition precedent is true]” or “if [a stated condition precedent is true]” or “when [a stated condition precedent is true]” may be construed to mean “upon determining” or “in response to determining” or “in accordance with a determination” or “upon detecting” or “in response to detecting” that the stated condition precedent is true, depending on the context.

As used herein, the use of the term “about” applies to all numeric values, whether or not explicitly indicated. This term generally refers to a range of numbers that one of ordinary skill in the art would consider as a reasonable amount of deviation to the recited numeric values (i.e., having the equivalent function or result). For example, this term can be construed as including a deviation of ±10 percent of the given numeric value provided such a deviation does not alter the end function or result of the value. Therefore, a value of about 1% can be construed to be a range from 0.9% to 1.1%. Furthermore, a range may be construed to include the start and the end of the range. For example, a range of 10% to 20% (i.e., range of 10%-20%) includes 10% and also includes 20%, and includes percentages in between 10% and 20%, unless explicitly stated otherwise herein. Similarly, a range of between 10% and 20% (i.e., range between 10%-20%) includes 10% and also includes 20%, and includes percentages in between 10% and 20%, unless explicitly stated otherwise herein.

As used herein, “obtaining” data or information may include one or more of accessing, acquiring, analyzing, determining, examining, identifying, loading, locating, opening, receiving, retrieving, reviewing, selecting, storing, and/or otherwise obtaining the data or information.

As used herein, a “well” or a “wellbore” refers to a single hole, usually cylindrical when viewed in at least piecewise increments, that is drilled into a reservoir. A well may be drilled in one or more directions. For example, a well may include a vertical well or section of the well, a horizontal well or section of the well, a deviated well or section of the well, and/or other type of well or section of the well. A well may be drilled in the reservoir for exploration and/or recovery of resources. A plurality of wells (e.g., tens to hundreds of wells) or a plurality of well are often used in a field depending on the desired outcome.

A well may be drilled into a reservoir using practically any drilling technique and equipment known in the art, such as geosteering, directional drilling, etc. Drilling the well may include using a tool, such as a drilling tool that includes a drill bit and a drill string. Drilling fluid, such as drilling mud, may be used while drilling in order to cool the drill tool and remove cuttings. Other tools may also be used while drilling or after drilling, such as measurement-while-drilling (MWD) tools, seismic-while-drilling tools, wireline tools, logging-while-drilling (LWD) tools, or other downhole tools. After drilling to a predetermined depth, the drill string and the drill bit may be removed, and then the casing, the tubing, and/or other equipment may be installed according to the design of the well. The equipment to be used in drilling the well may be dependent on the design of the well, the reservoir, the hydrocarbons and/or other subsurface resources being produced, and/or other factors.

A well may include a plurality of components, including but not limited to a casing, a liner, a tubing string, a sensor, a packer, a screen, a gravel pack, artificial lift equipment (e.g., an electric submersible pump (ESP)), and/or other components. If a well is drilled offshore, the well may include one or more of the previous components plus other offshore components, such as a riser. A well may also include equipment to control fluid flow into the well (e.g., injecting fluid for waterflooding, injecting fluid for hydraulic fracturing, etc.), control fluid flow out of the well, or any combination thereof. For example, a well may include a wellhead, a choke, a valve, and/or other control devices. These control devices may be located on the surface, in the subsurface (e.g., downhole in the well), or any combination thereof.

In some embodiments, the same control devices may be used to control fluid flow into and out of the well. In some embodiments, different control devices may be used to control fluid flow into and out of a well. In some embodiments, the rate of flow of fluids through the well may depend on the fluid handling capacities of the surface facility that is in fluidic communication with the well. The equipment to be used in controlling fluid flow into and out of a well may be dependent on the well, the subsurface region, the surface facility, and/or other factors. Moreover, sand control equipment and/or sand monitoring equipment may also be installed (e.g., downhole and/or on the surface). A well may also include any completion hardware that is not discussed separately. The term “well” may be used synonymously with the terms “borehole,” “wellbore,” or “well bore.” The term “well” is not limited to any description or configuration described herein.

As used herein, “hydraulic fracturing” is one way that hydrocarbons may be recovered (sometimes referred to as produced) from a reservoir in an economic manner. For example, hydraulic fracturing may entail preparing a fracturing fluid and injecting that fracturing fluid into the well at a sufficient rate and pressure to open existing fractures and/or create fractures in the reservoir. The fractures permit hydrocarbons to flow more freely into the well. In the hydraulic fracturing process, the fracturing fluid may be prepared on-site to include at least proppants. The proppants, such as sand or other particles, are meant to hold the fractures open so that hydrocarbons may more easily flow to the well. The fracturing fluid and the proppants may be blended together using at least one blender. The fracturing fluid may also include other components in addition to the proppants.

The well and the reservoir proximate to the well are in fluid communication (e.g., via perforations), and the fracturing fluid with the proppants is injected into the well through a wellhead of the well using at least one pump (oftentimes called a fracturing pump). The fracturing fluid with the proppants is injected at a sufficient rate and pressure to open existing fractures and/or create fractures in the reservoir. As fractures become sufficiently wide to allow proppants to flow into those fractures, proppants in the fracturing fluid are deposited in those fractures during the injection of the fracturing fluid. After the hydraulic fracturing process is completed, the fracturing fluid is removed by flowing or pumping it back out of the well so that the fracturing fluid does not block the flow of hydrocarbons to the well. The hydrocarbons may enter the same well from the reservoir and go up to the surface for further processing.

The equipment to be used in preparing and injecting the fracturing fluid may be dependent on the components of the fracturing fluid, the proppants, the well, the reservoir, etc. However, for simplicity, the term “fracturing apparatus” is meant to represent any tank(s), mixer(s), blender(s), pump(s), manifold(s), line(s), valve(s), fluid(s), fracturing fluid component(s), proppants, and other equipment and non-equipment items related to preparing the fracturing fluid and injecting the fracturing fluid.

As used herein, the term “hydrocarbon” refers to a compound containing carbon and hydrogen atoms. Hydrocarbons may include liquid hydrocarbons (also known as oil or petroleum), gas hydrocarbons, a combination of liquid hydrocarbons and gas hydrocarbons (e.g., including gas condensate), etc. For simplicity, many examples in this disclosure relate to the production of hydrocarbons. However, this disclosure applies to other produced fluid (e.g., produced water from a well, produced water from multiple wells, etc.), such as produced fluid in a liquid phase, produced fluid in a gas phase, or produced fluid in a combination of liquid phase and gas phase.

As used herein, a “reservoir” refers to a subsurface rock matrix in which a wellbore may be drilled. For example, a reservoir refers to a body of rock that is sufficiently distinctive and continuous such that it can be mapped. A reservoir stores resources, such as hydrocarbons, in its pore space. Reservoirs may vary in geologic features, such as, but not limited to, porosity, mineralogy, geomechanics, permeability, fluid saturation, presence of fractures, geologic structure (e.g., folds, manipulated by tectonic processes), thermal maturity, diagenetic alterations, etc. As used herein, in some embodiments, a reservoir may have a permeability of nanodarcy permeability to millidarcy permeability. The term reservoir may sometimes be used synonymously with the term “subsurface reservoir” or “subsurface formation” or “subsurface formation” or “subsurface volume of interest” or “subterranean formation” or “subsurface” or “formation” or the like. Indeed, the terms “hydrocarbon”, “reservoir”, and the like are not limited to any description or configuration described herein.

As used herein, an “unconventional reservoir” or “unconventional formation” generally requires intervention in order to recover hydrocarbons at economic flow rates or volumes. For example, an unconventional formation includes reservoirs having an unconventional microstructure in which fractures are used to recover hydrocarbons from the reservoir at sufficient flow rates or volumes (e.g., an unconventional reservoir generally needs to be fractured under pressure or have naturally occurring fractures in order to recover hydrocarbons from the reservoir at sufficient flow rates or volumes).

In some embodiments, the unconventional formation can include a reservoir having a permeability of less than 25 millidarcy (mD) (e.g., 20 mD or less, 15 mD or less, 10 mD or less, 5 mD or less, 1 mD or less, 0.5 mD or less, 0.1 mD or less, 0.05 mD or less, 0.01 mD or less, 0.005 mD or less, 0.001 mD or less, 0.0005 mD or less, 0.0001 mD or less, 0.00005 mD or less, 0.00001 mD or less, 0.000005 mD or less, 0.000001 mD or less, or less). In some embodiments, the unconventional formation can include a reservoir having a permeability of at least 0.000001 mD (e.g., at least 0.000005 mD, at least 0.00001 mD, 0.00005 mD, at least 0.0001 mD, 0.0005 mD, 0.001 mD, at least 0.005 mD, at least 0.01 mD, at least 0.05 mD, at least 0.1 mD, at least 0.5 mD, at least 1 mD, at least 5 mD, at least 10 mD, at least 15 mD, or at least 20 mD).

The unconventional formation can include a reservoir having a permeability ranging from any of the minimum values described above to any of the maximum values described above. For example, in some embodiments, the unconventional formation can include a reservoir having a permeability of from 0.000001 mD to 25 mD (e.g., from 0.001 mD to 25 mD, from 0.001 mD to 10 mD, from 0.01 mD to 10 mD, from 0.1 mD to 10 mD, from 0.001 mD to 5 mD, from 0.01 mD to 5 mD, or from 0.1 mD to 5 mD). The permeability of a particular formation can be determined by averaging measured permeability values from a series of representative core samples obtained from the formation. The formation may also be divided up into one or more hydrocarbon zones, and hydrocarbons can be produced from each desired hydrocarbon zone.

As used herein, a “conventional formation” may have a permeability higher than that of an “unconventional formation.” The permeability of a particular formation can be determined by averaging measured permeability values from a series of representative core samples obtained from the formation.

As used herein, it is understood that when combinations, subsets, groups, etc. of elements are disclosed (e.g., combinations of components in a composition, or combinations of steps in a method), that while specific reference of each of the various individual and collective combinations and permutations of these elements may not be explicitly disclosed, each is specifically contemplated and described herein. By way of example, if an item is described herein as including a component of type A, a component of type B, a component of type C, or any combination thereof, it is understood that this phrase describes all of the various individual and collective combinations and permutations of these components. For example, in some embodiments, the item described by this phrase could include only a component of type A. In some embodiments, the item described by this phrase could include only a component of type B. In some embodiments, the item described by this phrase could include only a component of type C. In some embodiments, the item described by this phrase could include a component of type A and a component of type B. In some embodiments, the item described by this phrase could include a component of type A and a component of type C. In some embodiments, the item described by this phrase could include a component of type B and a component of type C. In some embodiments, the item described by this phrase could include a component of type A, a component of type B, and a component of type C. In some embodiments, the item described by this phrase could include two or more components of type A (e.g., A1 and A2). In some embodiments, the item described by this phrase could include two or more components of type B (e.g., B1 and B2). In some embodiments, the item described by this phrase could include two or more components of type C (e.g., C1 and C2). In some embodiments, the item described by this phrase could include two or more of a first component (e.g., two or more components of type A (A1 and A2)), optionally one or more of a second component (e.g., optionally one or more components of type B), and optionally one or more of a third component (e.g., optionally one or more components of type C). In some embodiments, the item described by this phrase could include two or more of a first component (e.g., two or more components of type B (B1 and B2)), optionally one or more of a second component (e.g., optionally one or more components of type A), and optionally one or more of a third component (e.g., optionally one or more components of type C). In some embodiments, the item described by this phrase could include two or more of a first component (e.g., two or more components of type C (C1 and C2)), optionally one or more of a second component (e.g., optionally one or more components of type A), and optionally one or more of a third component (e.g., optionally one or more components of type B).

Unless defined otherwise, all technical and scientific terms used herein have the same meanings as commonly understood by one of skill in the art to which the disclosed invention belongs. All citations referred herein are expressly incorporated by reference.

Although some of the various drawings illustrate a number of logical stages in a particular order, stages that are not order dependent may be reordered and other stages may be combined or broken out. While some reordering or other groupings are specifically mentioned, others will be obvious to those of ordinary skill in the art and so do not present an exhaustive list of alternatives. Moreover, it should be recognized that the stages could be implemented in hardware, firmware, software or any combination thereof.

The foregoing description, for purpose of explanation, has been described with reference to specific embodiments. However, the illustrative discussions above are not intended to be exhaustive or to limit the invention to the precise forms disclosed. Many modifications and variations are possible in view of the above teachings. The embodiments were chosen and described in order to best explain the principles of the invention and its practical applications, to thereby enable others skilled in the art to best utilize the invention and various embodiments with various modifications as are suited to the particular use contemplated.

	Number	Date	Country
	63605923	Dec 2023	US
	63637987	Apr 2024	US

SYSTEM AND METHOD FOR NUMERICAL SIMULATION FOR FRACTURE DRIVEN INTERACTION

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CPC

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