Abstract Natural rock fractures can be tensile, shear, or mixed-mode while coalesced faults are characterized by shear. The smooth manufactured fractures that are conventionally studied in laboratories do not capture the hydromechanical properties of the rough-surfaced fractures that are ubiquitous in nature. Here, we employ triaxial direct-shear to investigate the hydromechanical properties of fractures that are created and maintained at in-situ stress conditions. Our results show that in-situ created fractures are rougher, leading to higher frictional strength and more tortuous transport properties than the values available in the literature. The in situ created fractures are very rough and heterogeneous with peak-to-peak amplitude that can be larger than 3 mm for a 25 mm length of fracture. In contrast, manufactured fractures often have less than 1 mm amplitude roughness. The difference in fracture roughness causes significant differences in hydromechanical properties. For example, the apparent frictional strength of in-situ created fractures is usually larger than 1 and shearing causes significant damage to asperities, which creates fines. In comparison, manufactured fractures exhibit strengths around 0.7 and produce relatively fewer fines. For fluid flow, the ratio of hydraulic aperture over mechanical aperture for in-situ created fractures is much smaller than 1 (e.g., 0.001), while the literature values are often larger (e.g., 0.01-1). This highlights the importance of considering the effect of higher surface roughness when modeling subsurface fracture mechanics and fluid flow. Introduction Characterizing shear slip on natural fractures of unconventional reservoirs can contribute to induced seismicity predictions, fault stability analysis, stimulated fracture fluid conductivity estimates, and shale gas production predictions (Meng et al., 2021). Most previous research used manufactured fractures, e.g., saw-cut fractures or tensile fractures, to study the hydromechanical behavior of shear on fractures in unconventional reservoir rocks. These planar fractures were smooth, unlike natural fractures. Such simple fracture surface geometry makes the hydromechanical measurements more easily repeated and controlled. This work on planar fractures produced important fundamental findings such as frictional stability-permeability relationships (Fang et al. 2017), mechanical and transport properties relationships (Schwartz et al. 2019), and fracture friction influence on induced seismicity (An et al. 2020).

Abstract This paper describes a series of tests designed to evaluate how perforating variables such as penetration, number of charges, phasing, and orientation affect fracture initiation. Average Permian basin conditions were used in this laboratory test study. In this basin, the vertical in-situ stress is significantly larger than the horizontal stresses. This stress regime increases the chances of axial fracture initiation and high near-wellbore fracture tortuosity. Optimizing these perforating variables can result in lower breakdown and treatment pressures, a reduction of near-wellbore fracture tortuosity, and, ultimately, more clusters with productive hydraulic fractures. Over a dozen perforating and hydraulic fracturing tests were performed in a polyaxial stress frame to simulate a horizontal well in the minimum stress direction in the field. A special concrete blend mixture with a compressive strength of approximately 8,000 psi was used to make the 18×18×18-inch blocks. A 2.9-in. wellbore, 2.38-in. casing, 1.56-in. gun, and shaped charges with 1-, 2-, and 6-in. penetrations were used to scale the field conditions. Gun phasing included spiral, in-plane, and oriented. The casing was cemented under stress equivalent to field conditions of 1,000-psi overbalance. The fracturing fluid viscosity and pumping rate were designed using dimensional analysis and numerical simulations to replicate a typical hydraulic fracturing operation in the field to produce similar fracture opening width and near-wellbore behavior. This led to fracturing with glycerin at 10 cm 3 /min. The test results clearly show that different perforating strategies affect fracture initiation geometry and pressures: 1) In-plane perforating enhances transverse fracture initiation. 2) Spiral perforating resulted in multiple transverse fractures. 3) Oriented perforating in the vertical direction produced axial fracture initiation with medium breakdown pressure and a medium propagation pressure. 4) Oriented perforating in the horizontal direction produced transverse fracture initiation with high breakdown pressure and low propagation pressure. 5) A perforated openhole test representing poor cement conditions showed low fracturing pressures with mixed axial and transverse fractures. 6) Larger penetration helped reduce breakdown pressure. This study shows how operators can use laboratory testing to optimize their unconventional perforating strategy, reducing fracturing pressures and near-wellbore tortuosity, which can lead to more efficient fracturing operations. Very few published hydraulic fracturing laboratory studies included properly scaled fracturing parameters, casing cemented under stress, and perforations made by real shaped charges.

Abstract One of the challenges of tight well configurations commonly used in the Permian Basin is well interference. The main factors controlling the degree of interference are the extent of depletion for a well and the spacing between interfering wells. In this work, we quantify and implement depletion and spacing in the analysis of well interference and predict the degree of well interference based on production data and geomechanical properties for Wolfcamp wells in the Delaware Basin (DB). Previous studies on parent-child well interference frequently use a characterization of spacing that may not accurately capture the complexities of well geometries and multi-well configurations. We propose a new spacing metric, based on 3D geometries of the wells and the overlap of the depleted volumes, that tackles these limitations and quantifies the extent of the interfering region for multi-well horizontal pads. We also proposed a new parameter that integrates the effects of depletion and geomechanical properties of the formation to predict the stress reorientation due to pressure depletion and consequently well interference in multi-well pads. The methodology is based on the estimation of production depletion and initial horizontal stress anisotropy of the formation. We characterized the fluid in place and identified fluid types, then estimated and mapped the amount of depletion based on production data and fluid properties. The results show the trend of depletion and population of high-producing wells across the basin. We estimated the initial horizontal anisotropy for the basin based on relative principal stress magnitudes and estimation of the minimum horizontal stress. The minimum horizontal stress was found to be accurately estimated using instantaneous shut-in pressure data. The results show that, for instance, anisotropy in Wolfcamp A Formation increases from 1,000–1,500 psi in the western DB to 2,000–3,000 psi in the eastern DB. We used the estimated values of depletion and initial horizontal anisotropy to calculate the ratio of depletion to initial horizontal stress anisotropy. The results show that the higher this ratio, the higher the stress reorientation and the higher the well interference. Therefore, the ratio of depletion to initial horizontal stress anisotropy can be used as an indicator of the severity of well interference. Although the analysis in this paper was based on the Wolfcamp of the DB, the approach can be extended to other formations and basins. In this paper, we quantified the degree of stress reorientation and, consequently, well interference using the ratio of depletion to horizontal stress anisotropy. This interpretation allows for identification of regions that are more susceptible to well interference and will serve as a guide to planning infill well drilling and predicting productivity of future infill wells.

Abstract This study corresponds to the second part of a paper series detailing the evolving approaches developed to improve project economics in Vaca Muerta shale formation ( Lerza et al., 2020 ). The main objective of this work is to develop a methodology that overcomes the well-known limitations of currently existing workflows that attempt to optimize well spacing and well completion design for maximizing project value in shale and tight (S&T). Currently published workflows on this topic generally fail to capture the interactions existing between well spacing and completion design, therefore the results obtained from applying those work steps are only optimal under a given completion design or well spacing assumption. However, most of the times, we are interested in finding the unconstrained global optimal solution rather than the local optimal solution offered by current methodologies, for which a simultaneous study of well spacing and completion design is required. The proposed methodology consists of applying fracture and reservoir simulation to calibrate a base model by history matching fracture and production data. Next, Design of Experiments technique is leveraged to ensure most of the interaction across the previously selected parameters are correctly captured while minimizing the number of required runs. Lastly, a machine learning model is built and tested from the gathered reservoir simulation results, and later used to efficiently obtain the predicted results for 1 million possible development alternatives comprising different combinations of completion and well spacing parameters. Finally, from the vast number of scenarios run, the one that offers the desired value of the target value metric and is also operationally achievable gets selected. By following the suggested methodology, the asset development team was able to find and propose an operationally executable development alternative that is expected to almost double the current wells Expected Ultimate Recovery (EUR) per section, while reducing the current discounted unit development cost between 10 and 30%.

Abstract Known for its highly anisotropic character, the Tuscaloosa Marine Shale (TMS) is an economically challenged formation in need of improved stress estimates. To avoid steep declines in production, hydraulic fracturing is used to release the hydrocarbons trapped in the matrix of the shale. Hydraulic fracture propagation and the overall hydraulic fracturing process depend on an accurate estimation of Young's modulus and Poisson's ratio. Moreover, to predict stress in horizontal laminated shales, several vertical transverse isotropic (VTI) models were proposed since ANNIE. However, such analytical methods require extensive calculations and knowledge of dynamic-to-static ratios when estimating mechanical properties from well logs. Machine learning (ML) can be applied to generate geomechanical synthetic logs and therefore, may represent an alternative to the current anisotropic techniques. In this paper, the Gradient Boosting algorithm is used to estimate the static properties of the Tuscaloosa Marine Shale. The ML model is trained on a dataset containing conventional and geomechanical logs from two wells. The latter are obtained using an extension of the ANNIE method which handles the difference between the vertical and horizontal Poisson's ratios by employing empirical correlations from ultrasonic core data for the stiffness coefficients C 13 and C 11 . To assure training data reliability, dynamic-to-static conversion ratios are applied and triaxial experimental data are used to validate the results. To predict the static mechanical properties of the shale formation, the proposed ML model uses the depth to account for compaction and three additional predictor features represented by the compressional slowness, and vertical and horizontal shear slowness logs. The model successfully predicts the vertical and horizontal Young's moduli and Poisson's ratios, as well as the minimum horizontal stress. The coefficient of determination (R 2 ) and normalized root mean square error (RMSE) are used to assess the performance of the model on the test dataset. Best R 2 (0.99) and normalized RMSE (0.015) are obtained for the horizontal Young's modulus and minimum horizontal stress, respectively, while lowest R 2 (0.96) and highest normalized RMSE (0.035) are computed for the vertical Poisson's ratio and vertical Young's modulus, respectively. Moreover, the model is used to estimate the static properties of a third TMS well without geomechanical logs. The predicted well logs show a good match to the available triaxial core data points, proving the applicability of the proposed model to the evaluation of the Tuscaloosa Marine Shale. Machine learning eliminates all tedious steps associated with the calculation of stiffness coefficients and the need to convert dynamic properties to static. The presented ML model can be run in most well log analysis platforms by anyone who disposes of a complete suite of sonic logs and seeks to better understand the mechanical properties of other TMS wells. This work creates a bridge between analytical methods and machine learning. Both petrophysical and geomechanical input was necessary, while results can further aid completion engineers in selecting the best intervals for hydraulic fracturing.

Abstract A machine learning-driven workflow has been designed to provide drilling engineers and geosteering geologists with a high-resolution earth model populated with elastic, petrophysical or geomechanical properties to assist with safe and efficient drilling. The technology can be deployed pre-drill or in real-time as a well is being actively drilled. The real-time deployment affords ahead-of-the bit and away-from-the-bit awareness that may help to mitigate pre-drill sub-surface uncertainties. Examples include shallow water flow, shallow gas, depleted formations, and the presence of salt. These phenomena may all cause excessive non-productive time (NPT) or may cause the wellbore's possible loss in extreme circumstances. Introduction A subset of a 3D prestack depth imaged seismic data covering 51 square miles (132 km 2 ) acquired in Midland and Upton Counties, Texas, was used in this study. Wireline log data from seven wells were made available. Five of the seven wells were incorporated in the training model and the two remaining wells were retained as "blind" tests for validation purposes. Results were achieved in three weeks with a significant increase in resolution compared to seismic data (60 ft to 15 ft). In this study, a suite of pre-drill attributes was generated. In addition, a simulated drilling scenario demonstrating the real-time deployment of the method is also described.

Abstract Understanding the geomechanical response of reservoir discontinuities is important for predicting permeability enhancement and is a primary factor in sweet-spot identification, containment assurance, and fault reactivation. Most reservoirs are naturally faulted and fractured to some extent, but the orientation and patterns of natural discontinuities are not consistent across reservoirs or even within a reservoir due to heterogeneous structural deformation. Based on experience working numerous case studies spanning unconventional and conventional fractured reservoirs, a specialized toolkit was created to streamline analysis of the interdependence of structural position, stress state, and natural fracture orientation. This paper summarizes an analytical modeling approach that combines fault stress analysis and natural fracture prediction and addresses three fundamental aspects of the geomechanical behavior of discontinuities. These techniques are implemented as modules in a specialized Matlab code that allows for complete customization and flexibility for ongoing geomechanics research. Geologic horizons and fault surfaces from outcrop or subsurface (e.g., seismic) field data and knowledge of the background state of stress are assumed as inputs. The first technique is to calculate the 3D displacement and strain fields due to tectonic deformation (forward kinematic modeling), as well as tectonic or in situ stress perturbations caused by faulting, folding, or hydraulic fracturing. The software uses triangular elastic dislocation methods to solve for the stress and strain fields. The second technique calculates resolved stresses on multiple input geologic surfaces based on the far field or locally perturbed stress states. Understanding the orientation of geologic discontinuities with respect to structural position and if they are likely to slip in shear, dilate, or close is useful for predicting reservoir permeability enhancement, fault leakage, microseismic susceptibility, and bedding stability. The third technique uses the 3D stress perturbation solutions to predict the orientation of natural fractures and faults throughout the field as a function of heterogeneous structural deformation. Three modes of fracturing are incorporated which are predicted at every observation grid node: tensile joints, conjugate shear fractures, and polymodal shear fractures. Combining the above techniques into a streamlined tool is helpful for addressing a range of structural geology and geomechanics reservoir problems. A few examples are highlighted to demonstrate the toolkit and applicable geologic problems.

Abstract Shale fabric is defined by mineralogy, organic components, and porosity networks and is influenced by depositional, biogenic, and diagenetic processes. Quartz fabric within shale is the focus of this work due to often high abundances of quartz, textural diversity, and influence on reservoir properties. Here we present an X-ray diffraction (XRD)-based technique to quantify sub-micrometer quartz properties and highlight its application in optimizing geomechanical predictions. Crystallite size peak broadening in XRD data occurs when the average size of the coherent X-ray scattering domain is < 1 μm, resulting in mineral-specific peak broadening. In this study, we quantify and evaluate quartz crystallite size for shales from 6 wells covering three onshore U.S. basins to determine if these data can be used to infer quartz origin and, in turn, quantify quartz texture. Geochemical and XRD data were collected on >150 samples and scanning electron microscope (SEM) images and porosity data were acquired on a subset of samples. Geomechanical impulse hammer data were collected on slabbed core, providing near continuous physical property data. From impulse hammer data, calculated plane strain modulus values ( E* ) were paired with mineralogy, geochemical, porosity, and quartz crystallite size data from similar depths. Multiple linear regression models were generated for each well dataset to assess the dependence of E* on bulk mineralogy and porosity data, with and without quartz crystallite size data. On a well-by-well basis, crystallite size was compared to Si/Zr data where high values of this elemental ratio have been shown to indicate authigenic silica inputs. We observed correlations (R 2 =0.32-0.87) with negative slopes between crystallite size and Si/Zr X-ray fluorescence (XRF) data, indicating that small crystallite size corresponds to higher authigenic/detrital quartz content. These data were supported by SEM image analysis, where samples with low average crystallite sizes were dominated by fine-grained matrix (authigenic) quartz, and samples with large average crystallite sizes contained mostly blocky, detrital quartz. Multiple linear regression results using only mineralogy data to predict E* yielded R 2 values between 0.04-0.82. However, inclusion of quartz crystallite information by modifying quartz content by a normalized crystallize size value improved the overall regression, yielding adjusted R 2 values up to 0.90. These findings provide a promising new method for 1) semiquantitative evaluation of quartz fabric and 2) improved geomechanical prediction models based on XRD derived data. Mineral fabric evaluation in shales helps to constrain depositional and authigenic history and provides insight into why reservoir properties may vary, despite having similar mineralogy. The method described in this study can be used to evaluate quartz fabric through quantifying the average, sub-micron quartz texture. Utilizing quartz fabric information within geomechanical models can improve the accuracy of models generated from low cost and rapid mineralogy datasets collected from cuttings, thus expanding the understanding of how reservoir properties impact hydrocarbon production in shale reservoirs.

Abstract The Caney Shale is emerging as a target for hydrocarbon production, creating opportunities to study rock mechanical origins of observed/anticipated challenges to effective and sustained stimulation. Here we examine five subunits within the Caney, two of which are dubbed "ductile" and three of which are dubbed "reservoir" rock types. The "ductile" versus "reservoir" identification is initially based on elastic properties ascertained from well logs. By comparing core-based mechanical tests, it is found nominally ductile and reservoir layers do not differ in terms of brittleness, but instead the nominally ductile layers tend to be weaker and more prone to creep deformation compared to the nominally more brittle reservoir layers. This difference in mechanical properties is shown to generate higher susceptibility to proppant embedment in the weaker and more creep-prone layers. Specifically, over a 5-year period, the creep is expected to have little impact on reservoir layers but is predicted to reduce propped fracture aperture by a factor of 2 in the ductile layers. Introduction The Caney shale is located in southwest Oklahoma, located below the Springer shale and above the Woodford shale formations (Cardott, 2017). Recent attention has turned to the Caney as an emerging target for hydrocarbon production. Some of the main challenges are thought to be related to high clay content (Awejori et al, 2021, Radonjic et al, 2020) and the presumably ductile behavior with negative implications for effectiveness of stimulation. However, recently it has been argued (Benge et al, 2021) the Caney is not demonstrably "ductile" by the typical measures of brittleness/ductility ascribed to rocks. Hence, a more thorough mechanical study is required to highlight challenges associated with stimulation/production from the Caney so solutions can be developed to suit the specific challenges. Firstly it is necessary to revisit what is meant by the terms "brittle" and "ductile". While such terminology is often used in a casual sense, there are at least two relevant mechanical definitions. One definition compares the peak and residual strength of a material (Bishop, 1967). Brittle materials lose strength abruptly when subjected to stress (i.e. tensile and/or shear) which exceeds the peak strength of the material, while ductile materials maintain a residual strength which can be nearly equal to the peak strength. Another definition has its roots in fracture mechanics, with brittle materials considered to ascribe to the assumption inelastic strain is confined to a very small region near a propagating crack tip (as compared to the crack length) and the energy required for crack propagation is assumed to be an intrinsic property of the material (e.g. see discussion in Papanastasiou and Atkinson, 2015).

Abstract Reliable interpretation and prediction of mechanical stratigraphy is the cornerstone of geomechanical investigations at multiple scales and in different applications. While lithological and petrophysical facies have been used in reservoir characterization to associate with storage capacity and flow characteristics of rocks, mechanical stratigraphy and its role is less known and more complex to identify. Mechanical stratigraphy modeling is the identification and interpretation of geomechanical rock types, which deform distinctly in response to changes in the subsurface system. These changes could occur naturally over geological time due to pore pressure buildup and plate boundary interactions or may be induced through field operations including drilling, hydraulic fracturing, water flood, production, thermal operations and depletion. The different geomechanical rock types will have a combination of lithologies and will often have overlapping petrophysical properties which together lead to variations of stiffness and strength. In this paper, the fundamentals, significance and geomechanical workflows for mechanical stratigraphy modeling are presented and discussed. In addition, evidence of mechanical stratigraphy in the subsurface for unconventional and conventional plays are shown. Applications of mechanical stratigraphy for hydraulic fracture barrier identification, well integrity, wellbore stability and subsurface containment assurance are presented. Introduction All subsurface operations such as drilling, injection and production lead to rock deformation and potentially failure in the reservoir and overburden intervals over the lifespan of a field. While some of these impacts are operationally manageable, in many cases it is critical to predict these changes by properly characterizing the geomechanical properties of the rock during the planning stage. This can help with appropriate design of operations such as injection pressure and mud weight design and mitigate potential geomechanical risks. At the regional scale, mechanical stratigraphy of the rock influences the faulting and folding over geologic time. In compressive settings, the contrast between different geomechanical rock types determines the form and extent of structural features. In extensional settings fracturing is mainly controlled by the mechanical properties of the host formation [1].

Abstract Previous studies and field production data have demonstrated that one of the most significant factors of the lateral well productivity and performance is the location of the landing depth; a few feet can make the difference between a good well versus an average or poor performer. To determine the best landing zone or zones, an assessment of the reservoir quality (RQ)—which encompasses petrophysical properties such as porosity, permeability, saturation, and total organic carbon (TOC)—and completion quality (CQ)—which encompasses anisotropic mechanical properties and horizontal stress calculations-is performed. RQ and CQ are determined using advanced petrophysical measurements and interpretation whereby sophisticated sonic wireline tools feature prominently in the workflow. However, operational efficiency is an overriding priority in the development of unconventional plays, allowing very little time between logging the vertical section and the start of drilling operations of the horizontal section of the well. With this in mind, both RQ and CQ analysis must be performed in the shortest time possible. Sonic data processing and interpretation along with fully 3D planar hydraulic simulations to predict fracture geometry are the identified bottle necks in the workflows due the amount of processing time needed. In this paper, we benchmark an improved workflow that utilizes the latest in digital borehole sonic services that provide accurate compressional, shear, and dipole shear anisotropy from the wellsite using new robust algorithms. A multimode (flexural and Stoneley) physics-based machine learning inversion is used to determine anisotropic constants accounting for mud speed variations in the borehole to obtain the anisotropic (transverse isotropic) mechanical properties and horizontal stress profiles. This data is then used for a novel stimulation design tool built natively on the cloud to model hydraulic fracture geometry as mechanical information becomes available. The improved workflow integrates the petrophysical and sonic data as input to the hydraulic fracture simulator by streamlining the data manipulation from the wellsite to final application. This workflow reduces processing time three-fold and increases the accuracy of anisotropic constants by understanding mud acoustic velocity variations. This workflow ultimately enables operators to take informed decisions in a timely manner without compromising efficient operations.

Abstract Individual well performance in the Marcellus Shale of northeastern Pennsylvania varies markedly, even in areas where the lithology, fluid composition, and completion design are consistent. A primary reason for this is the natural fracture system, which influences hydraulic fracture growth, dynamic fluid flow, reservoir pressure and stress behavior. Chief Oil and Gas (Chief) contracted Schlumberger to conduct an integrated study using an innovative modeling approach to quantify the impact of these natural fractures on field development. Working together, the team created an approach that consisted of constructing and coupling three models: a 3D geomechanical model, an unconventional fracture model (UFM), and a 3D dynamic dual-porosity model. The geomechanical model is composed of a discrete fracture network (DFN) containing both regional (J1 and J2 sets) and tectonic fractures. These are interpreted from seismic attributes (anisotropy azimuth, seismic velocity anisotropy) and ant tracking. The UFM model simulates the growth of hydraulic fractures and their interaction with natural fractures in the DFN. Portions of the natural fracture network are assumed to be open tectonic fractures, and their flow properties adjusted (porosity and permeability) to match well performance. Adjustments are also made to account for production-related perturbations in dynamic stress magnitude and azimuth, which impact later wells. These modifications to the fracture network are critical for history matching the dual-porosity model. The production history match showed that hydraulic fractures and open tectonic natural fractures are key production drivers in the study area, and that the spatial variability of the natural fracture network exerts more influence on well performance than initially thought. The connection between the hydraulic fracture network and portions of the open tectonic natural fracture system enhances parent well access to larger drainage areas. This controls the strongly variable well production observed in the study area. Subsequent stress perturbation resulting from parent well depletion is detrimental to the completion efficiency of the child wells, even with better frac designs with higher proppant loading. The modeling work also shows that the gas-in-place is consistent with volumetric and rate transient analysis (RTA) estimates. The coupling of the three models reasonably approximated changing reservoir conditions and created a nexus of domain expertise including geology, geophysics, geomechanics, stimulation, completions engineering and reservoir engineering. This enabled an understanding of the complex reservoir behavior of the naturally-fractured Marcellus Shale and generation of an optimized fit-for-purpose development plan. Chief was already implementing changes in spacing and putting more distance between offset PDP (Proved Developed Producing) wells and this study affirmed that revised development plan.

Abstract Optimizing completion efficiency has been one of the most challenging aspects of unconventional reservoir development. Two of the key factors to consider in completion design are stage length and cluster spacing, which affect both well performance and economics. Shorter stage length and tighter cluster spacing could create fractures with smaller widths and consequently lower proppant concentrations as a result of inter-cluster stress shadowing. On the other hand, longer stage length and wider cluster spacing, despite their economic benefits, can impair well performance by leaving unstimulated rock between two created fractures. Operating companies have taken different approaches, from trial and error to advanced diagnostics, to find the right balancing point for stage and cluster configuration. Ultimately, production analysis dictates the success. The main goal of this paper is to show the characteristics of cluster and stage length variations using production data in the absence of completion diagnostics. To this end, numerical modeling using typical values of reservoir and fracture characteristics in the Permian Basin was done. Multiple pairs of wells in the Permian Basin with similar reservoir properties and completion design but with different cluster and stage spacing were analyzed to validate the observed signatures. The conceptual numerical model results show that the wells at wider cluster spacing (and longer stage length) exhibit longer linear flow duration, which does not necessarily result in a larger stimulated area. Also, tighter cluster spacing and shorter stage length, which result in higher early time rates, only indicate acceleration, but this does not translate into improving long-term, economically justified performance. Higher matrix permeability (as a proxy for the existence of natural fractures) helps with larger stimulated regions under similar linear flow duration in wider cluster spacing (and longer stage length). However, this study shows significantly higher permeability might be needed for efficient stimulation of rocks between fractures in the case of wide cluster spacing. Production analysis of different well pairs in the Permian Basin using this workflow shows that cluster and stage length configuration can only be efficiently and effectively optimized by taking subsurface parameters such as stress, reservoir heterogeneity, and in-situ fluid into account.

Abstract Defining the producing height of a hydraulically fractured horizontal well drilled in multilayer systems has been one of the most challenging problems in unconventional reservoirs due to the lack of reliable direct measurements, specifically pressures from observation wells. Inaccurate characterizations of fracture height could result in either overcapitalizing the project or not draining the reservoir efficiently. The objective of this study is to show how vertical pressures from a monitoring well can be used to define the producing height of a hydraulically fractured horizontal well, calibrate the modeled hydraulic fracture geometry, and constrain reservoir simulation model input. Once calibrated, fracture and simulation models aid in predicting the depletion pattern around each individual well (vertically and laterally), which can directly affect stacked development scenarios. In summary, we are promoting drilling observation wells, but we also understand that it is capital intensive. We did correlate the monitoring well pressures to microseismic event counts, which is a cost-effective way to utilize the fracture shape. We tested the correlation with microseismic event counts in multiple pressure monitoring wells in Permian Basin and we found the correlation to be impressive. Yet without the basic data from the observation wells, mishaps will occur more often. This project utilizes a reservoir analysis workflow to narrow the range of fracture geometry uncertainty, and a vertical monitoring well drilled within the SRV of a horizontal well in the Permian Basin, which was producing for about 3 years as a standalone well prior to pressure monitoring. Multiple gauges installed at different depths in the vertical well monitored the pressure of each zone during the production of the horizontal well. In order to better understand these observations, numerical simulation was used to history match the production profile of horizontal well as well as the pressures of each gauge. A stochastic analysis was performed using different combinations of rock properties and fracture geometries for each geological zone. The modeling results were compared against other diagnostic tools. The depletion pattern along the vertically contacted layers revealed an astonishing insight into fracture dynamics. The pressure data also revealed the complex nature of layer contribution, with multiple build-ups and drawdown in layers above and below the landing and smooth continuous drawdown in layers within and adjacent to the horizontal well landing. Integrating the gauge pressure data into stochastic simulation workflow narrowed the range of uncertainty for rock and fracture properties significantly. The recovery factor estimated from simulation also varies vertically, dominated by fracture and reservoir properties of each zone providing key understanding of the fracture height and the nature of vertical drainage. Several diagnostic tools, including microseismic imaging from offset wells and well logs, are combined with the multilayer pressure measurements to better understand the drainage height in comparison to the monitoring well. In this project, we show that some of these diagnostics are insightful; however, they still need to be adjusted with well performance as a part of an integrated workflow. The learnings from this study are tremendously useful in optimizing vertical and lateral spacing of unconventional wells across all areas of the Permian Basin.

Abstract Hydraulic Fracturing Test Site-2 (HFTS-2) is a field-based research experiment performed in the Wolfcamp Formation of the Permian (Delaware) Basin. This paper focuses on integration, advanced geological characterization, and 3D subsurface modeling of the comprehensive HFTS-2 dataset. The study showcases a multidisciplinary reservoir characterization approach that incorporates geology, petrophysics, geochemistry, geomechanics, microseismic, and subsurface engineering analysis. Subsurface characterization of organic-rich mudstone formations requires understanding complex hydraulic fracture network growth in relation to inherent lithology, geomechanical properties, and interaction with pre-existing natural fractures. This paper presents a characterization workflow incorporating pre- and post-stimulation subsurface data, unique to the HFTS-2 dataset. The study integrated: (1) rock properties from logs, cores, and thin sections; (2) natural and hydraulic fracture descriptions from cores and image logs; (3) local and regional stresses; (4) geomechanics; (5) microseismic; (6) fiber optic (FO) and bottomhole pressure gauge (BHPG) response; and (7) produced fluids analysis. During a stimulation treatment, creation of the stimulated rock volume (SRV) is influenced by several subsurface factors. Key contributing factors include structural context, stress conditions, lithology, facies architecture, pre-existing natural fractures, and geomechanical properties. The HFTS-2 subsurface data integration indicates that the SRV is comprised of a complex juxtaposition of hydraulic fracture swarms, as evidenced by image logs analysis, core description, and microseismic monitoring. The HFTS-2 microseismic event density was used to generate 3D heat maps that serve as a representative SRV footprint, corroborated by secondary datasets. These maps were further integrated with petrophysical and geomechanical characteristics, as well as responses from FO and BHPG, to estimate the lateral and vertical dimensions of the effective fractures. The geological characterization for the HFTS-2 dataset combined with 3D modeling for petrophysical and geomechanical properties provides a strong foundation for subsurface simulation and optimization studies. The workflow improved our understanding of HFTS-2 hydraulic fracture propagation and characteristics in relation to offset pressure depletion and interaction with pre-existing natural fractures. Analysis showed that fracture geometry varies by stage and by well, and a complex fracture network is generated with varying fracture density. The multidisciplinary workflow presented herein for integration and characterization serves as a foundation to evaluate completion efficiency and estimate areal and vertical stimulation and depletion extent for the project. The workflow and learnings can also be transferred to other unconventional plays.

Abstract The goal of this study is to propose a predictive model for earthquake frequency at the Azle area, North Texas using detailed fault slip modeling and coupled fluid flow and geomechanical simulation. The model is then used to quantitatively assess the potential for induced seismicity from fluid injection/hydrocarbon production activities We built a site-specific seismological model based on the fault frictional energy from the simulation model and the observed earthquakes. The proposed approach provides a general workflow to assess the potential for induced earthquakes under various production/injection scenario. The flow and geomechanical simulation models were built, incorporating detailed fault geometry and horizons based on seismic survey. The flow simulation model was first calibrated by history-matching well responses of 70 producers and two injectors. Next, the calibrated pressure was mapped onto the geomechanical simulation model where the faults are represented as discontinuous surfaces to accurately represent the fault slip. The resulting fault frictional energy was correlated with the observed earthquakes in the area to build a site-specific seismological model. The seismological model was designed to predict the frequency of earthquakes with magnitude larger than 1.5, using the frictional energy from the model as input. A data-driven non-parametric regression technique, the Alternating Conditional Expectation (ACE) algorithm, is used to build a robust correlation between the fault frictional energy and the frequency of earthquake events (Mw > 1.5). Next, the seismological model is used to predict earthquake frequency under various injection scenario. The uncertainty in the areal extension of the fault is examined using sensitivity analysis in the flow simulation model. With increasing areal extent, the fault acts like flow barrier, delaying the pressure communication across the fault. This delay changes the timing of the peak frictional energy, implying that the earthquakes in the basement were induced by poro-elastic effect, not direct interaction with fluid pressure. Using coupled flow and geomechanical modeling, an empirical seismological model is built to predict earthquake frequency in response to fluid injection/production activities. The model helps assess and manage potential induced seismicity and associated risks at various operational scenarios of hydrocarbon production from shale reservoirs and disposal of by-produced water.

Abstract Effective stress represents the external load carried by the rock itself being a function of confining stresses and pore pressure. Confining stresses can be calculated from elastic rock properties, while effects of pore pressure, requires knowledge of the Biot-Willis coefficient, estimated from the more fundamental building blocks of a rock mass, that go beyond the elastic domain. These include the petrophysical properties from which components of the rock mass such as its pore space, frame and solid phase can be assembled from its constituent parts. In this study, we estimate the effective stress from seismic data using a combination of elastic properties estimated from an AVO inversion and petrophysical parameters estimated from a rock physics inversion of seismic data from the Montney in NE British Columbia, Canada. Introduction Assuming a relaxed basin with zero tectonic strain, the effective minimum horizontal stress used in engineering drilling design and hydraulic fracturing is given by (equation (1)) where σ v is vertical stress, ν is Poisson's ratio, P p is pore pressure and α is the Biot-Willis coefficient. The first term right of the equality in equation 1, represents the lithostatic loading estimated by integrating density to obtain the vertical stress multiplied by a ratio of Poisson's ratio. The 2 nd pore pressure term includes the Biot-Willis coefficient that is given by (equation (2)) where K d is drained bulk modulus at constant pore pressure and K s is solid bulk modulus. The limits on α occur at zero porosity for the lower bound and at critical porosity (Nur et al., 1998), for non-frame supporting grains in suspension representing the upper bound. At zero porosity, K d = K s and hence, α=0, resulting in a null pore pressure effect. Above critical porosity, the suspended grains become infinitely compressible at K d =0 and hence, α=l. This represents the maximum pore pressure effect for soft sediments near critical porosity, whereas consolidated rocks have values of α<1. The drained and solid phase bulk moduli required to determine the Biot-Willis coefficient, can be calculated from petrophysical component properties of the rock mass such as its pore space, frame and solid phase, estimated from seismic data via a rock physics inversion. First a calibrated rock physics model is required to define relationships between elastic and petrophysical properties. Subsequently, a rock physics inversion is run to estimate total porosity and various mineral fractions, from which K d and K s can be obtained. This was then used along with the elastic properties estimated from the AVO inversion to determine the effective minimum horizontal stress. Theory and/or Methods: AVO and rock physics inversion First, we derive a set of rock physics relationships between our elastic and petrophysical properties. Here, we use a regression-based model to estimate the effective bulk modulus, K, and shear modulus, G , for a three mineral mixture of quartz, clay and limestone with varying porosity and fluid saturation values. Any variable that potentially influences the rock matrix is used as a regression variable (e.g. effective pressure or stress), which allows for calibration to log data capturing local trends of the field as well as enforcing theoretical models. The rock physics model for M ={ K,G } is given by (equation (3)) where M 0 is the regression variable, M i is the i th mineral moduli, V i is the i th mineral fraction, M fluid is the fluid moduli (zero for shear) and f is the total porosity. The elastic and petrophysical logs are then used as inputs to estimate M 0 in addition to the moduli of the mineral end members of clay and limestone. Since clay and limestone are essentially "effective" end members consisting of various clay (e.g. illite and smectite) and carbonate (e.g. calcite and dolomite) minerals, these values must be determined from the data. Figure 1 shows the rock physics trend lines for total porosity and volume of limestone in acoustic impedance and Vp/Vs space.

Abstract Understanding fracture height growth can be of great significance to optimizing field development and improving recovery. The Hydraulic Fracturing Test Site 2 (HFTS-2) has provided a unique opportunity and an advanced dataset to allow us to observe and understand fracture geometries rigorously. Low-frequency distributed acoustic sensing (LF-DAS) data from a vertical well in HFTS-2 showed three key observations: (i) excessive upward height growth (>1000 ft) and limited downward growth of the hydraulic fractures during pumping, (ii) considerable additional upward fracture height growth (~300 ft) after well shut in, and (iii) very complex LF-DAS strain rate patterns for a small fiber-to-stage offset. Advanced geomechanical modeling was performed to simulate the hydraulic fracture propagation and the resulting strain responses in the vertical direction. The modeling results demonstrated asymmetric upward and downward fracture height growths as observed in HFTS-2 with a similar upward height growth rate. Simulated waterfall plots of vertical strain rate showed distinct patterns for different fiber-to-fracture distances. The upward-growing fracture tip can be clearly identified by the interfaces between compressing and extending zones. It was also found that the complex strain rate patterns observed in HFTS-2 for small fiber-stage offsets were not caused by the mechanical layering but possibly result from the simultaneous propagation of multiple hydraulic fractures at different rates. The simulation results improved the understating of the HFTS-2 LF-DAS data and the simulated strain rate patterns could also serve as templates for fracture height interpretation from LF-DAS data in future. Introduction While hydraulic fracturing is critical to unlock the potential of unconventional reservoirs and has been carried out for many decades, challenges still remain in understanding fracture propagation and estimating final geometry in the subsurface. With increased horizontal lateral length and decreased cluster spacing design, these challenges have become greater. Understanding how a fracture propagates and knowing the final fracture extent is crucial for optimizing completion design and well spacing to improve ultimate recovery. Furthermore, fracture height growth has been long recognized as difficult to measure and estimate due to its dependency on numerous factors such as stress and stress barriers, mechanical stratigraphy, weak interfaces / bedding planes, etc.

Abstract Estimates of in situ stresses and their changes upon production can be greatly influenced by the choice in poroelastic parameter values such as Biot coefficient and pore compressibility. In the determination of these parameters, grain compressibility and its anisotropy have emerged as the most difficult quantities to ascertain. The objective of this study is to investigate the microstructural controls on the effective grain compressibility as measured in the laboratory at close to in situ conditions, with the dual goal of incorporating microstructural information into grain compressibility estimates and producing better interpretations of laboratory measurements. A suite of ten samples from Bone Spring and Wolfcamp Formations covering a range of compositions was measured in the laboratory for anisotropic static elastic properties, including grain compressibility. A microstructural study involving X-ray radiography and SEM imaging was then carried out to investigate the contributions of texture (phase distribution and load bearing fraction) and fabric (anisotropy) to effective anisotropic grain compressibility. The measurements reveal anisotropy in directional grain compressibility of up to 70%, which, when combined with the anisotropic rock elastic moduli, produced values of Biot coefficient between 0.4 and 0.8 with up to 30% anisotropy between the horizontal and vertical directions. Mineralogical information points to a possible control of the clay fraction on the grain compressibility anisotropy. The microstructural study was thus conducted with a focus on testing the clay contribution hypothesis. While the fabric at the sample scale does not appear to be a strong contributor to the measured rock and grain elastic anisotropy, high resolution SEM imaging suggests a close relationship between pore space morphology as a proxy for the abundance of 'wet' clay aggregates, and effective grain elastic anisotropy. Our findings suggest that anisotropic grain stiffness values might be meaningfully inferred using microstructural information as well as mineralogy and density, thereby providing a rapid tool for the determination of poroelastic parameter sets in shale where direct measurements are not available.

Abstract Success completing a horizontal well commonly relies on the identification of major changes in rock types and rock properties, which are sometimes associated with faults or fractures crossing the well path. The present project has focused on ways to delineate these important events in Montney horizontal wells using gas and cuttings composition as well as reservoir pressures. New approaches have been defined for three types of data. Gas chromatography (C1-C6+) has been analyzed looking at the coherency of the various gas molecules against each other. Anomalous cuttings composition, mainly XRF based, have been mapped together with the coherency of the cuttings composition of successive samples using the calcium-manganese relationship. A different view with respect to pressure has been introduced using a 3-D analysis of the DFIT data. These combined approaches provide a mean to identify structural discontinuities that are not necessarily visible on seismic data, but need to be accounted for to optimize the well stimulation design, both from a production and a safety perspective. In the Eastern part of the Altares Field, a 3-D view of 13 DFIT measurements delineated 5 blocks with similar but shifted reservoir pressure gradients linked to compartmentalization. The density of data points led to proposing four faults roughly parallel to each other. However, these faults had not been recognized on the 3-D seismic. Available detailed analysis of the cuttings for some of the wells revealed local spikes in elemental composition that can be linked to precipitation of hydrothermal minerals. Each of the identified spikes was in agreement with the location of the faults proposed based on DFIT interpretation. Finally, the existence of these faults was also substantiated by gas compositional changes along the horizontal borehole, based on coherency parameters derived from Pixler plots and on sharp changes of the iC4/nC4 ratio. Each of the three approaches is new as DFIT are always analyzed by stratigraphic intervals, not in a 3-D approach; for the cuttings, our work defined a variety of hydrothermal indicators and the statistical analysis allowed to extract the outliers and reveal the faults. The coherency of the gas composition allowed to identify zones of leaking, zones of sealing and zones of major changes in gas composition; indicating faults. Detail of the coherency approach is illustrated with a series of examples. Identification of faults and compartments in a horizontal borehole can significantly help in the completion design by avoiding faults and defining frac stages with similar rock properties. The results of the work on the Altares field clearly show the value of interdisciplinary cooperation and integration as each of the techniques has, not only, corroborated the validity of the fault map but also provided key information to further characterize those hypothetical faults (e.g. hydrothermal fluids, sealing or non-sealing…).