Abstract As development has matured in Devon's Eagle Ford asset, the focus has shifted from primary development to late life optimization. The optimization options that are considered include: drilling of infill wells in the Lower Eagle Ford Member; drilling of redevelopment wells in the Upper Eagle Ford Member; and refracturing of existing wells. Remaining questions for the upside potential are: 1) What is the right development pattern for these different opportunities? 2) How would infills, redevelopment wells, and refracs interact? and 3) What is the impact of primary depletion in all these scenarios? Multi-well reservoir modeling is suited to answer these questions by considering the full lifecycle, wellbores, and the unit. This case study focuses on reservoir modeling of two pads in DeWitt County, Texas to investigate the production dynamics of multiple refractured wells and to capture the inter-well connectivity among refractured parents and several redevelopment wells. For this purpose, a history matched simulation model with nine (9) horizontal hydraulically fractured wells was developed. Within the modeled area, five parent wells produced for about 5 years prior to four of them being refractured. The fifth parent well was only repressured prior to the completion of new redevelopment wells. Immediately after the parent wells were refractured, the four redevelopment wells were zipper fractured. Besides the stimulation information, bottomhole pressure gauge data from multiple wells was available for model calibration. A 3D static reservoir model that integrates multi-disciplinary data from geology, petrophysics, geomechanics and engineering was utilized. A fully implicit dual-porosity reservoir simulator with special geomechanical features was used for the calibration, in which the temporal change in mean stress for each grid cell is implicitly solved together with pressure and the other flow variables using poro-elastic information. This simulator dynamically solves for fracture generation (rock deformation) and dilation of tensile fractures, as well as the subsequent fracture closure upon depletion and re-dilation of fractures as a function of net stress. The calibration effort consisted of matching the performance of all wells during the hydraulic fracturing, flow back, and depletion periods, including daily historical oil, gas, and water production rates together with the bottomhole pressure data. Predictive runs were performed to examine different development scenarios and to provide decision support for pattern optimization. Simulations performed on the calibrated model significantly enhanced our understanding of fracture propagation in the presence of prior depletion, the dynamic nature of horizontal and vertical inter-well connectivity, and the role of refracturing in pattern development. Additionally, the study provided an assessment of refracturing operations as a mitigation strategy and an analysis of the interaction among the existing and newly created fracture networks, including how such networks are tied to the refractured and infill well performance. We demonstrate that opportunities remain in the developed sections of the Eagle Ford resource, depending on the existing wellbore geometries, prior depletion, and varying fracture geometries dictated by reservoir geomechanics and legacy completions.

Abstract An ongoing challenge in unconventional reservoirs is the significant production degradation (loss of production) realized from child wells drilled adjacent to depleted parent wells. One strategy hypothesized to reduce the realized degradation is to modify the completion design in the child well. The main objective of this case study will be to test this hypothesis and quantify the impact completion design has on child well degradation; specifically, the case focuses on the stage architecture component of completion design defined as the combination of cluster spacing, number of clusters per stage, and stage length. This paper covers an integrated, multi-disciplined review of a unique development situation in the Permian where three different depletion scenarios surround a single well at various well spacings. This data rich review will characterize the SRV (Stimulated Rock Volume) and DRV (Drained Rock Volume) from each of four completion designs within the different depletion scenarios. Data sets include fiberoptic DAS/DTS (Distributed Acoustic/Temperature Sensing) and microseismic during stimulation, along with downhole pressure gauges, chemical tracers, downhole camera for perforation erosion, additional fiber-optic DAS/DTS production logs, and interference (well communication) tests. A single well with four different completion designs surrounded by three different depletion scenarios creates a rare opportunity to analyze the impact completion design has on child well degradation. Eight different forms of data acquisition technologies were used to increase understanding of completion variable impacts to SRV and DRV as well as validate several new cost-effective data acquisition technologies that were successfully trialed for this pilot. The SRV-related data shows fracture interference with offset depletion, but the amount of interference did not conclusively change among the various completion designs tested. Similarly, DRV-related data shows child well degradation when exposed to parent well depletion, but the amount of degradation did not conclusively change among the various completion designs tested. This suggests that factors other than stage architecture are the dominant drivers of well performance. Detailed analysis from the cross-functional team provides multiple perspectives on the results acquired as they pertain to the overall motivating objectives of the pilot.

Abstract This paper provides the theoretical and practical basis for application of multi-segment Arps production decline models, particularly for multi-fractured horizontal wells used to develop ultra-low permeability resources. Two- and three-segment Arps models have been used in the industry for production forecasting, but the application is usually based on empirical observations and intuitive assumptions. This paper provides the basis for dividing production history of these wells into at least four segments. We first examined rigorous solutions to governing flow equations for idealized conditions and found the basis to expect (1) early transient linear flow with b ≡ 2; (2) a transition flow regime between transient and boundary-dominated flow (BDF) regimes with continuously changing b about one log-cycle in duration; and (3) BDF with b ≡ 0 for an incompressible fluid. We examined the basis for the Fetkovich type curve, which include BDF stems for compressible fluids with b values ranging from 0 to 1, and found evidence that, under most circumstances, b values should range from 0.4 to 0.5 for gas wells and 0.3 to 0.4 for depletion-drive oil wells. Durations of these flow regimes can be identified using log-log plots of pressure-normalized rate vs. time (preferable) or simply rate vs. time when pressure data are not available. Analysis of the Arps hyperbolic decline model indicates that straight lines with slopes = 1/ b are expected during times with unchanging b . We found that, for multi-fractured horizontal wells, at least four distinct flow regimes should ultimately appear in practice and are related to depth-of-investigation considerations: (1) an early ramp-up in production; (2) a transient flow regime which can last for years with essentially constant b , often near 2; (3) a transition flow regime, lasting for over a log cycle in time and with continuously changing b ; and (4) BDF, with essentially constant b , and 0.3 < b < 0.5 in most cases. Additional segments may arise because of changed operational conditions or flow into the stimulated reservoir volume (SRV) from the unstimulated matrix. There is no reason to expect a terminal b of zero except for the rare case of an incompressible fluid. For forecasting production from wells in resource plays, we should include the minimum of four flow regimes, even when only transient flow has been observed in history, and we should forecast appropriate durations of flow regimes and times at which they expected to begin and end based on considerations discussed in the paper. These considerations are fundamentally important for forecasting of individual wells and for construction of typical well production profiles (TWPs, akatype wells or type curves).

Abstract In this work, we analyze an extensive dataset of wells in the Delaware Basin to identify key factors affecting the performance of the new (child) wells. We propose depletion-volume-overlap idea as a new method for describing the spatial region of interference among communicating wells. This idea replaces the conventional 1D spacing which can have limitations when applied to non-ideal field situations and extends the concept to several wells with production interference. We formulate "depletion score" as an interference metric that includes the combined effect of reservoir depletion and spacing for tight oil wells. Data compiled for over 13,000 wells in the Delaware Basin was utilized to determine important features controlling well interference and to guide us to refine our definition for the depletion score. Using a machine-learning model, we assess the impact of the individual features on the productivity of new infill wells during the first year of production. The depletion score is conceptualized based on our results of 360 physics-based simulations, each conducted for a pair of parent/child wells considering different spacing and depletion conditions. The depletion score is defined as a non-linear function that depends on: (1) the overlap of depletion volumes around the parent and child wells; (2) the parent's cumulative hydrocarbon production; and (3) a fitting parameter p . We consider the damage to child-fracture propagation often caused by alterations to rock mechanical stress, which occur as a result of depletion around the parent well. We assume three scenarios: severe, moderate, and no geomechanical-induced damage. In addition to the depletion score, eleven features are defined and calculated for the child wells to serve as the input for different machine-learning (ML) regression models. The goal of the ML models is to infer the relationship between the input variables and the productivity of the child well relative to that of the parent well. Our results show that the interference metric is predictive of child-wells performance relative to the parent's performance ( R 2 = 84% - 89%) when compared against the simulation results. However, when fitted to the field data, the interference metric is not as predictive and explains only 9.8% of the variance. Production from the field depends on additional factors such as reservoir quality and completion conditions. As the additional parameters are considered, the random-forest model explains 97.9% of the variance for the training data and 38.8% for the testing data following an 80/20 train/test data splitting scheme. We interpret the results of the machine-learning model using SHapley Additive exPlanations (SHAP), which provides insights on the importance of individual features and their interactions in explaining the prediction. The results suggest that depletion score has the greatest impact on the child well's performance. This is followed by the injected fluid ratio, the original oil-in-place, and the proppant concentration ratio.

This paper extends the single well reservoir modeling concepts documented in Raterman et al. 2019 to a multiwell pilot. The analysis integrates multiple data sources to provide a holistic view of spatial drainage and interwell interference in a multiwell context. The pilot employed a four well staggered high-low configuration. All wells were kitted with bottom hole pressure and fiber optics. A vertical well was employed to monitor microseismic and pressure during the completion and production phases of the pilot. In-well and cross-well DAS, DTS and pressure data were integrated in a full pattern reservoir model to history match production, interwell interference and far field pressure data. The history matched model indicates that spatial drainage remains somewhat localized and patchy in the interwell context given the pilot spacing and completion designs. Interference between wells is significant and is largely mediated through high conductivity, limited volume conduits between wells. Although these conduits facilitate interference, a strong competitive drainage scenario between wells is not concluded. These insights are invaluable in determining the efficacy of the employed completion and spacing design; and suggest further improvements for future designs. Finally, the model was extended to analyze a Pump-into-Parent (PIP) test conducted in a partially depleted pilot producer. Fracture dilation was evidenced. Introduction In the quest for optimal well spacing and stacking configurations in shale plays, it is an oft-stated presumption that interwell interference is to be avoided (Fiallos, et al., Rucker, et al.). It is our experience, however, that communication between wells is established via hydraulic fracturing to distances routinely exceeding 1000 feet (Raterman, et.al., 2018); hundreds of feet beyond what would be considered an appropriate interwell spacing distance for tight rocks. Moreover, it appears that interwell communication is established fairly early in the pumping operation suggesting that even a radical alteration of the completion design may have limited impact on the outcome. Therefore, it would seem that the likelihood of interference is a fact of life and must be dealt with in the context of single well production degradation as a function of interwell distances, stacking configuration, completion design and potential parent well interactions.

Rate transient analysis (RTA) is an important method to predict productivity and reserves for reservoir and completion characterization in unconventional plays. In addition, multi-horizontal-well pads are a common development method for unconventionals. Close well spacing between multi-fractured horizontal wells (MFHWs) in multi-well pads results in significant interference from adjacent MFHWs. For RTA of production data from multi-horizontal-well pads, the influence of adjacent MFHWs cannot be ignored. In this work, we propose a semi-analytic RTA model for the multi-horizontal-well pad with arbitrary multiple MFHWs properties and starting production times. Combining Laplace transformation and finite difference analysis, we obtained a general solution of a multi-well mathematical model to use in RTA. Our model is applicable to cases of multiple MFHWs with different bottom hole pressures (BHP), varying hydraulic fracture properties, and different starting production times. In the solutions, we observe bilinear flow, linear flow, transition flow, and multi-MFHW flow. Rate normalized pressure (RNP) and its derivative are also affected by multi-MFHW flow. Two case studies revealed that the negative effect of interwell interference on the parent well productivity is closely related to the pressure distribution caused by the production of child wells. Introduction RTA allows us to predict oil and gas well production rates and reserves to characterize formations and effectiveness of completions. (Lee and Wattenbarger 1997). RTA requires only production data (rate and pressure) and does not require long-term shut-in for pressure build up tests, and as such, most research has focused on RTA in unconventional applications (Lawal et al. 2013; Sahai et al. 2015; Yadav and Motealleh 2017; Ravikumar and Lee 2019; Baek et al. 2019; Yuan et al. 2019; Chu et al. 2019b). Development of unconventional resources relies on horizontal drilling and multi-stage fracturing (Chun et al.2020). Infill drilling is also common. Operating companies usually prefer to concentrate drilling rigs to core areas. For example, Fig. 1 shows the distribution density of horizontal wells in Mountrail County, ND, and indicates that the well spacing among multiple MFHWs in the same horizon was as small as 660 ft (Krishnamurthy et al. 2019). For production data analysis of MFHWs in this kind of multi-well pad, interwell interference and connectivity have become realistic issues that must be considered (Anderson et al. 2016).

For most US unconventional resources development, operators usually first drill the parent wells to hold their leases. After several years, infill wells will be drilled. The Meramec stack play in Anadarko Basin, Oklahoma is a multi-layered tight oil reservoir and its development just followed this practice. The parent well was drilled in layer 3 and shut down after 2-year production for infill well completion in layers 3 and 4 (layer 4 is below layer 3). After the infill well completion, field observations reveal a sharp increase in water production of the parent well, a decline in the oil production rate from the parent well, and a significant difference in production performance emerged between newly drilled infill wells. Two infill wells that are closest to the parent well but landed in layer 4 yield much lower oil and gas production compared to other infill wells completed in the same layer. In this paper, field data were analyzed to investigate the root causes of production loss from the parent well and lower-than-expected production rate from these two infill wells for this staggered well layout. Landing depth, well trajectories, operation conditions, and completion designs were compared for all infill wells and we found out that none of these can cause the significant production difference among the infill wells. Hence, the most accepted hypothesis is that the stress change induced by parent well depletion negatively affects the effectiveness of infill well completion. A reservoir geomechanical simulation was developed to evaluate the pressure and stress change induced by the parent well depletion of two years. The reservoir model was prepared with available geological and well logging data. History matching for the parent well production was performed to determine the region of pressure sink. Based on geomechanical well logging test data, a 3D real field scale geomechanical model was built to calculate the stress redistribution induced by pressure sink. Results show that non-uniform fracture length with extreme long fractures in the parent well can generate non-uniform depletion area and pressure sink. Fractures generated in infill wells tend to propagate toward to depletion region and hit the existing long fractures in the parent well. Therefore, frac-hits still can be induced even with 1000 ft large well spacing. Stress change was also investigated vertically in different layers, especially layer 4. We found that stresses in the upper section of layer 4 have been decreased by parent well depletion and stresses in the lower section of layer 4 have been increased, which will favor fracture growing to the upper section and layer 3 due to lower stresses. Therefore, the staggered well layout may not necessarily be an effective strategy to mitigate interwell interference. This study helps understand the poor performance of infill wells and provides some suggestions for future well development, such as applying extreme limit entry or diverter to generate more uniform fracture growth to avoid irregular depletion region, placing the parent well in the lower layer to mitigate well interference between staggered parent and infill wells for development of multiple pay layers.

Data science techniques have proven useful with the high volume of data collected in unconventional reservoir development workflows. In this paper, we present an analytics and machine learning use case for operations to minimize deferred production and quantify long-term production impacts due to frac hits in the Bakken and Three Forks formation during infill development. The outcomes of this study used significant amounts of data to provide the operator with a more efficient shut in strategy that can contribute to saving capital expenses and optimizing the rate of return on investment. A workflow is presented that improves our approach to a shut in radius which is required when offset wells experience intense pressure spikes within a given radius during the stimulation of infill wells. These pressure spikes are caused by connecting the hydraulic fracture networks and at times can damage the structure of the well, promote sand production and/or impact post-completion production. To mitigate these impacts, operators may shut in all offset wells to help reduce pressure sinks nearby or use re-pressurization techniques such as high pressure/low rate injection. Determination of the shut in distance is often based on analogous operations and/or experience alone, and tends to be conservatively derived, potentially leading to the unnecessary shut in of wells that may otherwise not experience any pressure event and may have been deemed low risk. Shutting in too many wells can be the largest expense incurred by a new completion, as operators not only work-over the offset wells, but also defer production for the entirety of the completion job. On the other hand, an underestimated shut in distance might enhance fracture driven interferences (frac hits) during a completion job. The use case applied a workflow to a large field dataset. We underscore that historical data can be used to quantify the zonal communication and to provide recommendations for future operations regarding a shut in radius. With this novel approach, we analyzed several well pads in Bakken basin and all in close proximity. The analysis included the following datasets: static geological/formation data, completion data, one-second pressure data, and production history. The method used in this study can be defined as a 3-step process: 1) Employing analytics to assess and evaluate fracture driven interferences during the completion of new infill wells. 2) Quantifying the long-term production impact that may occur after shutting an offset well. 3) Applying machine learning techniques to determine the optimal offset distance and degree of communication. Pressure data from the offset monitoring wells were used to determine the presence of fracture driven communication between wells during a completion operation. Production data were also utilized to quantify the long-term impact of shut in and fracture driven interferences. Machine learning techniques were then applied to measure the influence of offset distance (and other parameters such as completion design, depletion history, and zonal variance) to communication. The results of the analysis indicated the distance at which communication occurs most often in offset wells from the hydraulic completion of new infill wells. Considering this information, an optimized shut in distance was proposed for offset wells in the area reducing it from the previous radius by 250-550 ft thus improving production metrics.

Models of hydraulic fracture propagation in the hydrocarbon industry have been traditionally based on boundary element methods, finite difference method, and recently supplemented by peri-dynamic continuum formulations. These methods commonly require extensive gridding accompanied by elevated capital investments to acquire the target resolution. This study applies a recently developed semi-analytical method, which is fast and grid-less, to model fracture propagation due to crack-face loading and crack-tip stress concentrations. The Time-stepped Linear Superposition Method (TLSM) allows for the visualization and quantification of the dynamic propagation of multiple hydraulic and natural fractures, while preserving infinite resolution by sidestepping grid refinement. By visualizing stress concentrations and predicting fracture propagation paths, the dynamics of fracture hits and fracture redirection can be investigated. Solutions solved by TLSM are benchmarked against independent studies to ensure physical and practical compatibility. The insight of how growth of hydraulic fractures may deviate from planar model conceptions will be useful to optimize fracture treatment plans. TLSM is used to model dynamic solutions for typical zipper fracturing completions, showing the effect of well spacing, and fracture spacing on the development of fracture hits and fracture redirection. 1. Introduction Hydraulically fractured horizontal wells have been at the forefront of hydrocarbon production in tight shale. The common objective for any horizontal well completion technique is to maximize the fracture network surface area within the reservoir. High number of perforations, tighter fracture spacing, and tighter well spacing, have all been used to increase fracture-surface exposure to petroleum-bearing rocks. While maximizing fracture network contact with pay zone is the objective of a fracture treatment plan, due to stress shadow effects, lower number of perforations could be more beneficial in complex fracture network creation (Fisher et al., 2004). A higher number of clusters may contribute to higher completion cost, which needs justification, especially when oil prices are depressed. In addition, the effect of well interference is magnified when wells are tighter spaced, which may adversely impact production rates (Roussel and Sharma, 2011).

The multistage hydraulic fracturing process is the main stimulation technique to develop tight gas and shale formations. Estimating fracture geometry and stimulated reservoir volume (SRV) is a focal parameter to judge the fracture operation and predict the well performance. RTA and PTA techniques usually assume uniform fracture half-length; however, the fracture length varies from cluster to another due to reservoir properties and stress shadow effect. This paper presents the performance of single-stage fracture systems with simple bi-wing fractures for all clusters and complex fractures systems which could be close to real fracture network with fixed SRV value. Numerical simulation is used to generate the production and shut-in data from the complex and simple fracture stage models. The production rates and shut-in pressure results from the simulation are then analyzed by RTA and PTA to estimate the stimulated area. The preliminary results showed that the complex system yields the same or better performance compared to the simple fractures system scenario depending on the formation properties. Generally, the estimated area from RTA and PTA (production surface area PSA) was less than the fracture surface area (FSA) that was used in the numerical simulation. A possible reason for this behavior is the interference between the created fracture on each cluster. As a result, the effective flow area was less than the actual fracture system area. In the case of slightly high permeability formations, the SRV parameter estimated from linear flow analysis in both RTA and PTA was higher in the complex fracture well. Besides, PTA diagnostic plots show a lower estimated skin factor (the difference between the pressure and its derivative curves) in the complex system. While in the case of lower permeability formations, the performance was the same in both scenarios. This study differentiates between the production surface area and the fracture surface area, and its behavior in complex and simple fracture systems. Therefore, the difference in production performance between wells with different hydraulic fracture systems could be used in understanding the spacing performance.

Shale field development strategies are aimed at increasing recovery factors and thus revolve around well-spacing decisions and hydraulic fracture treatment plans. The hydraulic fracture test site (HFTS) consortium provided invaluable data and insight in terms of the interaction between multiple wellbore pads. Although pressure communication between wellbores during completion and production has been analyzed in previous HFTS studies, relatively little work has been performed to constrain the actual reservoir volume being recovered—this paper addresses an integrated approach to assess the development of the drained rock volume (DRV) and recovery factors. A detailed analysis of flow regime changes, shows when the first fracture pressure interference occurs in each well, and also pinpoints the onset of inter-well pressure interference. Computation of the instantaneous b -value from well rate decline data reveals the occurrence of b -sigmoid patterns, which provide a more detailed indication of the onset of flow regime shifts and pressure interference (with adjacent fractures and well drainage boundaries). Typical changes in water-oil ratios (WOR) and gas-oil ratios (GOR) were also studied, in particular in conjunction with flow regime shifts and bubble point pressure flips during well shut-in tests. Understanding flow regime shifts related to (1) the diffusive advance of pressure transients, and (2) the convective growth of the DRV, can help design more efficient well spacing, cluster staging, perforation design, lateral length and landing targets, fracture design and geometry, etc. to increase hydrocarbon recovery factors. 1. Introduction The US Department of Energy (DOE) sanctioned in 2014 two major field test sites to study the effects of hydraulic fracturing when applied to hydrocarbon reservoirs with multi-well development. One field project was staged in the Eagle Ford Formation, in a lease region in DeWitt County, Texas (Raterman et al., 2018, 2019); the other so-called HFTS project was located in the Permian Basin (DOE award number DE-FE0024292) and studied well completions in the Wolfcamp Formation, in a lease region in Reagan County, Texas (Ciezobka et al., 2018). Both projects were enabled by consortia of participating companies and research institutions (such as NETL, UT Austin and BEG), matching the DOE funding with subcontracted services and in-kind contributions. The two projects were managed by the Gas Technology Institute based in Des Plaines, Illinois, a non-profit organization which develops, demonstrates, and licenses new energy technologies for private and public clients, with a particular focus on the natural gas industry.

Pressure depletion during the production stage could result in significant changes in the in situ stress and strain distribution in the subsurface formation, particularly in regions near the hydraulic fracture planes. Nevertheless, for the sake of simplicity, fracture properties are generally treated as static parameters, while the dynamic behavior of fracture closure is likely to be ignored. This simplistic approach often renders the modeling of interaction or interference between fractures to be incomplete. In this work, a discrete fracture model is employed, and the flow and geomechanical simulations are coupled. The discrete fracture model (DFM) is implemented in the MATLAB Reservoir Simulation Toolbox (MRST) – an open-source reservoir simulation software. Unstructured meshing is used to discretize the gridding domain, and the matrix-to-matrix, fracture-to-fracture, fracture-to-matrix fluxes are computed explicitly in the computational domain following the control volume formulation. The flow calculations are solved simultaneously with the geomechanical computations: the governing equations for poroelasticity are incorporated and the fixed stress splitting coupling methodology is employed. The results are compared with a base case, where the geomechanical effects are ignored. The potential effects of fracture interference on hydraulically fractured tight-gas well production are examined. Several case studies are presented to demonstrate the utility of the proposed coupling strategy for analyzing production performance in hydraulically fracturing reservoirs. This model takes into account the effects of poroelasticity and stress or strain variation in the fractured domains. Factors influencing the behavior of fracture interference are examined. Finally, an analysis of the computational costs is also presented. A novel model is implemented in the MRST framework to couple flow and geomechanical computations based on fixed-stress splitting in a DFN model. This simulation approach can more accurately capture the dynamic behavior of fracture closure and fracture interference in hydraulically fractured wells. The results illustrate the significance of incorporating geomechanical effects in the flow simulation process. Insights pertinent to the operational strategies are also highlighted based on the simulation results.

This study uses a machine learning framework to systematically analyze field production and completion data to understand the impact of frac-hits on parent and child wells and predict well spacing and completions design. Frac hits are one of the most pressing reservoir management issue that can enhance or compromise production over either the short-term or have sustained impacts over longer times. The extent of the impact is dictated by a complex interplay of petrophysical properties (high-perm streaks, mineralogy, etc.), geomechanical properties (near-field and far-field stresses, brittleness, etc.), completion parameters (stage length, cluster spacing, pumping rate, fluid and proppant amount, etc.) and development decisions (well spacing, well scheduling, etc.). As a result, the impact of frac-hits is not straightforward and difficult to predict. The study uses data from the Meramec, Woodford and Wolfcamp formations. We develop an automated machine-learning based frac-hit detection algorithm that also quantifies the impact on the parent and child wells using matched decline curve models. We analyze about 500 parent and over 1100 child wells in the three formations. Our results show that the key factors governing the extent of the impact are the extent of depletion and producing oil rate of the parent well before frac hit, completion design parameters (fluid and proppant amount) and well spacing. Our machine learning analysis generates regression models to predict the impact of frac hits. These regression models are coupled with economic analysis to determine optimum spacing for any given completion design or optimum completion design for any given spacing. The parent wells in all three formations had both positive and negative impact of the frac hits. Around 60–67% parent wells were negatively impacted while 33–40% wells were positively impacted. For the child wells, 71–85% wells were negatively impacted and 15–29% of the wells were positively impacted. Combining the impact on parent and child wells, the impact is dominated by the child wells as 69 to 82% of the parent-child pairs were negatively impacted and only 18–31% of the pairs were positively impacted. Considering percent loss in cumulative oil volumes in the next 5-years, in the Meramec, parent wells on average show a 16% reduction while child wells show a 39% reduction due to frac hits. The corresponding numbers for the Woodford formation are 19% and 37% and Wolfcamp formation are 20% and 22%, respectively. This translates to a parent well losing on average 40–50 thousand bbls in next five years and a child well losing on average 130–150 thousand bbls in the same period. This study systematically analyzes available data to understand the impact of frac hits and formulates a machine learning-based well spacing-well completions matrix workflow that can easily be extended to other formations by integrating commonly available production and completions data.

This study presents a holistic, multidisciplinary, and integrated geoengineering workflow that results in economic comparisons of different completion strategies on a 10 well pad spanning multiple reservoirs in the Delaware basin. The resulting economics are constrained by geophysical, geological, geomechanical, hydraulic fracture, and production forecast models validated at each step in the workflow. In the case of these wells, the completion design "Case 3" was identified as the best completion strategy from an economic standpoint, significantly increasing ROI and NPV. The planned frac order-- top-down, bottom-up, or optimized, had a varying impact on the overall economics of the pad, depending on the reservoir targeted, and a lesser impact as compared to the pump volumes and schedule--although in some geologic settings this impact could be much higher. By combining geophysical, geologic, and engineering information into geomechanical, hydraulic and fracture models, representative production forecasts and economic projections were made to optimize the strategy for this 10 well pad’s development. Introduction The tumultuous price environment which has persisted for the past five years is here to stay, further pressuring unconventional reservoir development to seek any and all efficiency gains. As technologies continue to optimize performance on the frac site, the last gasp of factory-mode drilling and production manifests as "cube development". Cube development is a capital-intensive strategy being adopted by a number of Permian basin operators that relies on financial efficiencies gained through the simultaneous drilling and stimulation of multiple laterals in multiple benches to enhance the economics of unconventional reservoirs. Such a large undertaking is complimented by predictive iterative modeling of constrained hydraulic fracture effectiveness and production forecasting to optimize as much as possible the stimulation in light of reservoir realities. In this case study, a 10 well cube, spanning the 3rd Bone Spring to the Wolfcamp B is evaluated in a comprehensive 3G (geophysics, geology, and geomechanics) and engineering workflow to characterize the reservoirs, their geomechanical response, the resulting hydraulic fracture conductivities, and production forecast to increase the ROI of the development. The integrated workflow after Ouenes et al. 2016 leverages seismic data, log data from wireline and surface drilling parameters, reservoir test, frac data, and historical field production data to build high-resolution 3D distributions of geologic properties which will constrain geomechanical simulations, hydraulic fracture designs, and the resulting production predictions. Technologies ranging from stochastic inversions of seismic data to produce high resolution impedance models, machine learning-driven geologic property modeling, MPM-based geomechanical simulation, and fast marching reservoir simulation represent some of the key methods which enable this evaluation to be conducted. The sequential geologic workflow distributes key reservoir properties of unconventional production drivers such as porosity, OOIP, elastic properties, pore pressure, and natural fractures in a sequential manner. This reservoir characterization then constrains geomechanical simulations to capture the interactions both vertically and laterally between the various wells, which is then passed as an additional geomechanical constraint with the geomodels to the hydraulic fracture simulations and production forecasts. Consequently, the engineering component of the workflow can be quickly iterated to understand the economic viability of various development strategies to maximize ROI while honoring realistic and varying reservoir properties.

This case study involves three infill (i.e., "child") wells drilled near a producing primary (i.e., "parent") well. All study wells target the same unconventional sandstone formation. The project objective is quantifying the interactions between the primary and infill wells. Such understanding will guide future development. The operator drilled five infill wells west of the primary well, two infill wells were drilled shallower than the three study wells. The primary well produced for seven months before the infill wells’ completions. Of the three study wells, Well 3 is closest to the primary well. To mitigate interference from the infill wells, the operator 1) shut in the primary well during infill stimulation and 2) fractured the infill wells in an east-to-west "zipper" order, starting with Well 3. To monitor communication among the wells, the operator placed a bottom hole pressure gauge in the primary well and pumped fluid tracers in Wells 2 and 3. For an understanding of fracture geometry, the operator monitored the infill well stimulations with microseismic, which measures the acoustic response of fracturing, and electromagnetic (EM) fluid tracking. EM fluid tracking uses Controlled Source Electromagnetics (CSEM) technology to measure the changes in subsurface resistivity caused by treatment fluid injection. Injecting fracturing fluid into the source rock alters a generated EM field causing measurable differences on the surface. As a result, the technique maps fluid movement over time. These results highlight when treatment fluid preferentially develops toward the primary well. Introduction After drilling a primary well, deciding how to optimally develop the remainder of any given acreage can be a daunting challenge. Supported by theory and experience, each technical individual in a multi-disciplinary team has their own operational "secret sauce" to achieve the best results. As fields mature, operators developing unconventional basins drill a higher percentage of infill wells than primary wells and most of those wells are simply not as productive as the primary (Schaefer, 2019). Understanding what factors drive well performance is critical for operators to succeed in the current low-price environment. Testing different completion designs through a trail-and-error method and waiting for production results is neither efficient nor likely to yield conclusive results. Thus, operators must gather data during completions to measure fracture development and qualify design effectiveness. Without corroborating measurements, pressure gauges alone do not provide a complete picture of what occurs downhole during completions.

Infill development typically strives to improve resource recovery while maximizing economic objectives of the organization. Success is dependent on many variables, several of which include well spacing, completion design, and mechanical stratigraphy. Optimizing development is contingent upon understanding how these variables interact with one another and what combination of development strategies will maximize the company objective. One of the challenges with optimizing horizontal multi-frac wells has been quantifying well to well connectivity, understanding the appropriate amount, and how various development strategies impact that relationship. This paper will present a case for development optimization by integrating the results of multiple quantitative pressure interference tests with completion design and well spacing in the STACK play. The framework for quantifying the connectivity between wells was developed by Chu et al (2018) and is often referred to as Chow Pressure Group (CPG). Using this technique, the Magnitude of Pressure Interference (MPI) was quantified between 25 horizontal wells within 10 development units. The dataset is unique because the infill units were developed with varying completions and well spacings which provides an opportunity to isolate and understand how each variable directly impacts well to well connectivity. This study also addresses the desired amount of connectivity between horizontal wells and how it impacts well performance and recovery. The results from this case study suggest there is a clear relationship between well spacing and MPI, consistent with the findings by Chu et al (2018). Ultimate recovery was investigated and found to have a correlation with the amount of connectivity between development wells. Additionally, at consistent well spacing, higher proppant volume per cluster increased MPI and Estimated Ultimate Recovery (EUR) per well. Increasing proppant per cluster is likely extending the conductive half-length, increasing fracture overlap and MPI, and reducing bypassed resource beyond the tips of the fractures, resulting in higher EUR and Drilling Spacing Unit (DSU) recovery. This case study provides asset teams with valuable relationships between reservoir, completions, geologic characteristics and how they tie to well performance in the Anadarko Basin. These relationships are expected to be different in every basin/formation, however, it highlights the power of quantitative interference tests in optimizing infill development and understanding the appropriate amount of well to well connectivity. This work also lays out a practical example regarding the dependent nature of completions and reservoir well spacing which can serve as a workflow for asset teams working unconventional plays across the world.

With signs of the shale boom slowing, the need to make informed decisions on asset development becomes increasingly critical in a competitive landscape. Yet the data for informed decision making is often spotty, particularly with regards to one of the industry’s greatest hurdles: maximizing stimulated reservoir volume with minimal investment. For many, the problems that underpin this hurdle are clear: improper well spacing, frac hits/stress shadowing, unsuitable connectivity between benches, and interwell interference/communication all well-established contributors to poor productivity and a non-ideal stimulated reservoir volume (SRV), a definitive strategy for the "best" way to develop different plays has not proven as obvious. One area that has seen sustained interest is the SCOOP/STACK play of the Anadarko basin. Since 2012, this geological region has proven one of the lowest-cost, highest margin plays in the U.S. With multiple stacked reservoirs, the effective stratigraphic trap of the area creates a continuous petroleum system with multiple development opportunities. In this study, non-radioactive liquid chemical tracers were pumped alongside stimulation treatments for dozens of wells placed in the Woodford, Meramec, and Osage layers. These tracers served to uniquely "tag" downhole oil and water phases, allowing the operator to quantitatively track the production of oil and water as well as their point of origin. On an individual level, these liquid tracers served as an effective production log, measuring changes in behavior over time. On a field level, however, the application of liquid tracers made it possible to evaluate bench-to-bench communication and the effect different completion designs had on interwell communication/interference. Multiple variables were considered, including the effect of geological features, frac order, well spacing, and parent pump-in protection to achieve an optimal completion strategy. This work shares many of the high-level lessons learned, providing a beneficial ROI by rapid fine-tuning of well spacing based on ongoing tracer communication over time.

Optimal well spacing remains one of the major topics of debate in the development of unconventional oil plays. There is still no consensus among operators with respect to the choice of an ideal development strategy. Some large operators with high-value acreage may apply conservative well spacing, confident about their ability to maximize recovery and present value per well without confronting the challenges of interference associated with denser spacing. Given that the market acknowledges the long-term acreage potential for these companies, this strategy allows to maintain investor confidence with no negative impact on enterprise value. Meanwhile, smaller operators may prefer aggressive down-spacing programs to maximize their asset’s value. In general, with the initial increase in the number of wells per spacing unit, NPV increases linearly while rate of return does not degrade. Once frac interference starts eroding well productivity, the rate of return starts declining. Yet NPV per unit still increases before productivity degrades too steeply. The optimal number of wells per section is found somewhere between these two inflection points. The exact choice will depend on operator or investor preference, which is maximization of either return or total value, the latter being more capital-intensive. This paper provides a comprehensive overview of the optimal spacing range for some areas of the Permian Basin (Midland North/South, Delaware Texas/New Mexico) and key landing intervals (different zones of Wolfcamp, Spraberry and Bone Spring). The results have significant practical value for E&P operators involved in the ongoing development of the Permian Basin. Previous research in the area was normally focused on individual case or operator studies. To our knowledge, this paper is the first attempt to address the choice of optimal well spacing in the whole Permian Basin. The results of the paper could be interpreted as Permian E&P playbook when it comes to the selection of well density.

The Second Bone Spring Sand is currently the second most drilled bench within the Delaware Basin. Some of the main struggles encountered by operators is determining the combined optimal well spacing, targeting, and completions design for a given bench. Moreover, to economically and efficiently develop any bench within the Permian, a strong understanding of reservoir heterogeneity is needed. Recent work has provided insight into the controls on Second Bone Spring Sand (SBSS) production and optimal development strategies. A key driver of well performance is reservoir architecture, and one must understand the spatial variability of their field area as it affects the overall development strategy that is ultimately deployed (i.e. completions design, well spacing, targeting, etc.). Furthermore, a deeper look into completions trends within the SBSS has closed the gap in optimizing dollars spent in relation to production gains. Introduction The Permian Basin of southeast New Mexico and west Texas has been a highlight of North American oil and gas exploration, development, and production for decades. This basin is further sub-divided into the Midland and Delaware Basins (Figure 1), which are separated by the Central Basin Platform. The Delaware Basin is bounded to the east by the Central Basin Platform, to the west by the Diablo Platform, to the north by the northwest shelf and to the south by Marathon-Ouachita orogenic belt. Formation of the Delaware Basin began with the Tobosa Basin (Galley, 1958) that existed from the Late Pre-Cambrian through the Mississippian, with compression and faulting during the Ouachita-Marathon Orogeny causing the Central Basin Platform to rise (Schumaker, 1992; Soreghan & Soreghan, 2013). Climate during deposition in the Delaware Basin was generally arid, with the basin resting at approximately 5-10 ° north of the equator (Soreghan & Soreghan, 2013; Ziegler et al., 1997). Sediment is thought to have been sourced via aeolian transport as well as via fluvial systems (Fischer & Sarnthein, 1988; Soreghan & Soreghan, 2013). Deposition in the Delaware Basin fluctuated between carbonate-rich highstand and silica-dominated lowstand conditions with high TOC mudstones forming farthest from the shoreline. This reciprocal sedimentation depositional history has led to mixed-lithology rock with highly variable facies, such as the Wolfcamp and Bone Spring Formations that are major targets of unconventional development today. The Leonardian Bone Spring Formation especially displays this lithologic alternation and is comprised primarily of three major siliciclastic members divided by carbonates that are named in order of increasing depth (Figure 2), in addition to regional members such as the Avalon and Harkey Mills Sandstone. This paper focuses on the middle siliciclastic member, the Second Bone Spring Sand (SBSS), which was deposited as a lowstand submarine fan system.

Abstract Well-to-well interference is an increasingly discussed issue. Previously drilled and producing “parent” wells and recently drilled “child” wells are yielding a reduction in recovery rates in both short and long-term cases due to interference. A primary contributor to the variability in production is the presence of pressure sinks as the result of production depletion in the parent wells. Infill drilling will continue to occur in the development of unconventional plays, and it is crucial to gain an understanding of the impacts of well-to-well interference on hydraulic fracture generation. This paper discusses a detailed approach to investigating well-to-well interference based on integrating hydraulic fracture modeling and reservoir simulation in two different formations, the Niobrara and Codell, in the Denver-Julesburg Basin. The geomechanical properties were calibrated by DFIT data and pressure matching of the parent well treatments. The resulting parent well fracture geometries were incorporated into a numerical reservoir model to determine the pressure depletion envelopes. The imported depletion model allows for the simulation of the child well treatments and associated impacts of the pressure sinks on fracture generation and the interaction between child and parent wells. The resulting depletion model provided a framework to investigate various methods to mitigate the effects of well-to-well communication in subsequent development. The developed workflow of well-to-well interference is applicable in understanding the effects of infill development in other producing basins. The modeled child well treatments resulted in a clear indication of well-to-well communication with the parent wells that was attributable to pressure depletion. Actual field bottom-hole pressure measurements validated these results in the parent wells captured during the time of the child well treatments. Resulting proppant concentrations of the child well fractures indicated that the majority of the proppant transports towards the parent wells. Very little effective conductivity exists in the opposing direction of the depleted regions. Slickwater treatment simulations indicate extremely asymmetric fractures that stay isolated to their respective target bench. For child wells in the same bench as the parent wells, fractures propagate directly toward the parent wells, with little to no fracture growth in the opposite direction. Protection frac simulations indicate beneficial or detrimental results depending on the amount of repressurization that is achieved and the distance that the pressure transient extends into the reservoir. Re-pressurizing the reservoir surrounding the parent wells by 1,000 psi resulted in a reduction of well interference. A 500-psi scenario resulted in increased well interference between the parent wells. Several wells communicated with both parent wells due to the repressurization being insufficient to offset the depletion. Natural repressurization of the reservoir to mitigate the effect of well interference was also investigated by using the reservoir model. Simulation of the parent wells being shut-in for three months prior to the child well treatments resulted in a pore pressure increase of only 280 psi. Based on the protection frac sensitivity of 500 psi, this is not a large enough repressurization to mitigate well-to-well interference successfully in the modeled scenarios.