The scope of this work is to introduce a technology that measures perforation effectiveness on a stage by stage basis before the hydraulic fracturing process begins. The measurement utilizes surface generated tube waves to interrogate the perforated section of the wellbore. We present three case studies demonstrating how "low perforation quality alerts" mitigate operational issues, achieving the deployment of appropriate stimulation treatments for several operators in the Eagle Ford, Haynesville, and Niobrara formations. The reflections of tube waves are analyzed to characterize perforation effectiveness on a stage by stage basis. This methodology is non-intrusive, infinitely repeatable and can be performed in the short time interval between removing the perforating equipment from the well and beginning the fracture treatment process. The operators in our study were alerted to stages with a high likelihood of pumping issues such as high treating pressure, screen outs, or low proppant volume placement. Real-time measurements flagged these stages as having poor wellbore connectivity to the reservoir. Prior to pumping, the operator and crew in the field were alerted to the stages that showed low perforation quality. This allowed modifications to the stage design, such as additional acid, sweeps, finer proppant, gel, increased pad, lower rate, or an additional perforation run. In the cases where changes were made to the design, the objective of mitigating pumping problems due to poor perforation performance was a success. In all the cases where preventive design changes were not implemented, downhole difficulties were experienced resulting in sub-optimal stage execution and/or screen outs. Cost savings in the range of $300,000 on some wells were achieved due to the mitigation of pumping problems associated with poor wellbore to reservoir connectivity. Perforation quality and reservoir rock geomechanics play a dominant role in hydraulic fracturing operational success or failure. Although there have been extensive studies focusing on the role that perforation diameter plays on treatment efficiency, these studies do not adequately consider the importance of the perforation tunnel (depth and quality of perforation penetration into the near well region). Having real-time, non-intrusive, field-based data that provides a direct measurement of this essential element can influence the execution of the hydraulic fracture design. This mitigates the costly exercise of recovering from a screen out and improves the likelihood of a productive stage.

Severe frac hit incidents were encountered during stimulating horizontal production wells in a pilot pad of a tight oil reservoir in Ordos basin. The reservoir is interbedded, highly heterogeneous both vertically and horizontally as result of gravity flow deposition. This raised a big concern on the stimulation treatment size and well spacing of the pad and further implication on the field development plan of the reservoir. A deep understanding of root causes and an effective frac hit prevention and mitigation strategy were much needed to address the problem. A multidisciplinary team was formed to investigate the problem. Initial analysis on the frac hit incidents showed that the frac hits were not correlated to well spacing, or stimulation volume as frac hits only occurred at certain stages out of those with the same stimulation volume or well spacing. Then the study turned the focus to investigating the problem from the geological and geomechanical perspective through leveraging a 3D high definition (HD) geological and geomechanical model. The detailed investigation revealed that the root causes of the frac hits were multiple folds: Existence of natural fracture corridors led to frac hit of wells in much longer distance. Alignment of hydraulic fractures among horizontal wells also increased the chance of frac hits as the result of alignment of perforations among horizontal wells. Asymmetrical propagation of hydraulic fracture (e.g., deviated to one side of horizontal laterals increased the chance of frac hit as the result of heterogeneous sand body and in-situ stress field.) Lack of vertical fracture containment resulted in the crossing-layer frac hits. With the good understanding of the root causes of frac hits, a frac hit risk map was generated based on the 3D HD geoscience model, which highlighted high frac risk zone in the pad. The frac hits observed from subsequent stimulations of the horizontal wells occurred only in the high frac hit risk zone, which validated the frac hit risk map. Based on the findings from the study, the frac hit prevention and mitigation strategy was developed.

The pressure decline data after the end of a hydraulic fracture stage is sometimes monitored for an extended period of time (30 minutes to hours). However, this data is not analyzed and often ignored or underappreciated due to a lack of suitable models for closure of propped fractures. In this study, we present a new approach to model and analyze pressure decline data that is available at the end of each plug and perf stage in horizontal wells. The new model, interpretation method and specialized plots presented in this study allow us to quantify closure stress, average pore pressure inside the stimulated reservoir volume (SRV) and normalized fracture stiffness/compliance evolution along the entire horizontal wellbore without additional data acquisition costs. Analysis of field stage-by-stage pressure decline data shows that the interpreted results are consistent with the analysis of DFIT data from an offset well for the same formation. We found that the early-time stage-by-stage pressure decline trend is controlled by progressive hydraulic fracture closure on the proppant pack, while late-time pressure decline reflects linear flow. Thus, the pressure decline rate alone is not a reliable indicator of the productivity or stimulation efficiency of a certain stage. When DFIT data is not available, pressure decline analysis of a main hydraulic fracturing stage can be used even if it can be monitored for a relatively short period of time (1 hour). Most important of all, we show that the slope of pressure derivative on a log-log plot and the normalized fracture stiffness plot can be used to infer the uniformity of proppant distribution.

Stage length and perforation cluster spacing are important design parameters for multi-stage hydraulic fracturing. This study aims to demonstrate that the interplay between subtle variations of the least principal stress (S hmin ) with depth and the stress shadows induced by simultaneously propagating hydraulic fractures from multiple perforation clusters, primarily determines the propped and fractured area in the target formations. This principle is illustrated with the help of a case study in a prolific unconventional formation in the north eastern US, where the vertical stress variations are well characterized through discrete multi-depth stress measurements and actual stage design parameters used by the operator are known. At first, we show how the hydraulic fracture footprint and proppant distribution varies with a change in the vertical stress profile. The stress profile is shown to be a very important in determining the optimal vertical and lateral well spacing. The evolution of the stress shadow in the different layers is shown during the pumping as the fracture propagates across multiple layer boundaries. Subsequently, we demonstrate that by changing the magnitude of stress perturbations caused by the stress shadow effect, the distribution of propped area can be altered significantly. We use this method to determine the optimal cluster spacing keeping other design parameters constant such as flow rate, perforation diameter, etc. Simulations from selected cluster spacing realizations are run with high and low permeability scenarios to show the importance of correct matrix permeability inputs in determining the three-dimensional depletion profile and ultimate production. By varying the cluster spacing we show the hydraulic fracture propagation change from being solely stress layering driven to stress shadow influenced. The effect of stress shadow on the final fracture footprint is highly specific depending on the given stress layering and is thus case-dependent. This study demonstrates that knowledge of stress variations with depth and modeling are critical for optimizing stimulation efficiency.

Initial hydraulic fracture simulation calibration in unconventional reservoirs is commonly done based on data acquired during Fracture Calibration Tests (FCT), and in a postmortem fashion from treatment data acquired in the field. After the well has been put on production, another independent piece of information becomes available through Rate Transient Analysis (RTA) which can be used to constrain and finetune the simulated hydraulic fracture geometries. Production data used for RTA and observed fracture treatment data from a well in the Turner formation have been utilized to effectively calibrate an integrated numerical modeling study of a representative well in the Powder River Basin Province and landed in the Turner formation. The RTA provides two independent parameters. The first being the A c √k from the linear flow regime, from which the total effective hydraulic fracture surface area, Ac is derived. The second parameter estimated from boundary dominated flow is the Stimulated Reservoir Volume (SRV). These two parameters are then used to constrain the hydraulic fracture simulations (with Ac) and the numerical flow model (with SRV). A two-folds feedback loop based on the available RTA interpretation allowed fast conjoint calibration and history matching of the hydraulic fracturing treatments and the long-term production performance. Numerical simulation results provided a final production history match achieved by constraining the effective drainage height (guided by geological observations), supported by the hydraulic fracture simulations and the RTA-derived information. Differences from RTA and numerical results are attributed to common RTA assumptions such as a homogeneous reservoir, single phase fluid, and constant fluid properties. The Turner formation in this area is relatively homogeneous, with the Carlile formation, a strong stress barrier, above and a highly laminated underlying Frontier formation. This led to the conclusion, that hydraulic fracture propagation downward into the Frontier was limited by the highly laminated rock and well contained within the Turner. Additional differences between the RTA and numerical results are attributed to the true complexity of the final hydraulic fracture geometry. RTA is an analytical solution for a set volume with geometric hydraulic fractures whereas these hydraulic fracture simulations are numerical and create varying geometries. Taking this concept a step farther, actual hydraulic fracture propagation will interact with natural fractures, localized stresses, and each other, creating an even more complex and hydraulic fracture geometry. Presented here is a novel application where the coupling of RTA and numerical simulation workflows has been successfully applied. A two-folds feedback loop based on RTA-derived parameters allows fast calibration and history matching of the hydraulic fracturing treatments and the long-term production performance. The independent hydraulic fracture surface areas and SRV are independently consumed, and results highlight impact of non-trivial geological features, such as stress barriers, laminations and lithological variability.

Rock mechanics triaxial tests and well logs are the main source for determination of mechanical properties of reservoir. These methods obtain values for mechanical properties corresponding to parts of the formation close to the well area. The experimental approach is much more limited as the coring operation is costly and is performed in a handful of appraisal/exploratory wells. Here, a novel methodology, geomechanical well testing, is presented to estimate the elastic and plastic mechanical properties using pressure transient testing. In the first part of the paper, the theory of poroelasticity was utilized to develop a geomechanical well testing technique, which attains estimation of reservoir's poroelastic properties. The technique is on the basis of developing a diffusivity equation incorporating mechanical deformation into the fluid transport in porous media and via applying different mechanical boundary conditions, one can obtain several closed-form solutions for storage coefficient. The developed storage coefficients, however, include Poisson's ratio (PR) as the target variable to estimate from conventional well testing. As a verification, a case study was conducted using the pressure transient data from a sandstone aquifer. Adopting the conventional well testing principles, three different values for PR were obtained. The first impression to this point was to decide which value is the most representing value for the aquifer under investigation. We envisioned two methods for this critical step: 1) comparison of obtained PR values from the geomechanical well testing technique with the one estimated via another reliable source such as well log/seismic and/or 2) comparison of pressure-time measurements with available numerical simulations. We took this finding for granted and devise a way to obtain an estimation of dominant boundary conditions of a reservoir. Once the dominant deformational behavior was assessed, the technique may be re-implemented along with future well testing measuements to monitor the evolutions of elastic properties during the life of reservoir. The second part of the paper deals with another geomechanical well testing technique, which provides a tool for estimation of strength properies through developing a generalized diffusivity equation using poroplasticity theory with a plastic potential function based on Mohr-Coulomb yield/failure criterion. An analytical solution was obtained under uniaxial strain assumption, which can be used to estimate internal friction angle or dilation angle.

Wellbore integrity analysis should consider the cement setting process in a confined downhole environment, noting that cement is initially a liquid that becomes a solid. In our study, the state of stress of cement specimens is measured during cure from a liquid to a solid at laboratory simulated downhole conditions. We apply accurate control of axial stress, confining pressure, and pore pressure inside cement specimens during the entire setting process combined with strain gauges mounted on the outer surface of the steel pipe to measure the cement's state of stress during the setting process. The setup allows multiple experimental conditions to be investigated, including constant axial stress, constant axial displacement, drained and undrained conditions. Different controlling conditions represent different field scenarios since the process of cement setting in the downhole situations is a highly complex process that depends on the in-situ condition, formation lithology, cement slurry composition, mud cake composition, drill bit type, etc. In this work, the Class-G cement slurry is cured under constant axial stress, confining pressure, and undrained conditions. This represents a field condition where the top of the cement can drop during setting, the vertical component of cement weight is not significantly affected by bonding, and the formation is quite impermeable with a very difficult fluid exchange between formation and cement. Our results show that under such a scenario, no significant pressure drop occurs after seven days of the setting process, and the cement initial total stress is close to its hydrostatic pressure.

In recent years, hydraulic fracturing design has evolved significantly. Fluid volumes injected in a lateral have more than doubled to ~ 250,000 bbl/well ( Weijers et al., 2019 ). Increased injection volumes coupled with a sub-optimal completion design can lead to over-stimulation at current well spacing densities. In many instances, dominant clusters that take a majority of the injected fluid during child well treatment intersect offset parent wells. This results in sub-optimal reservoir drainage, highly inefficient fluid and sand placement and negatively impacts the overall well productivity due to well interference. In this work, we analyze offset well pressure measurements in the Permian Basin to evaluate if a frac job is overstimulated. Additionally, we perform numerical modeling studies to evaluate the extent of overstimulation in different stimulation scenarios and provide recommendations to maximize the capital efficiency of a frac job. We analyze the pressure response in offset parent wells in the Permian Basin during treatment of a nearby well. Fracture arrival times (time taken for the child well fractures to intersect with a nearby parent well) are investigated for multiple stages during child well stimulation. This information from field data is coupled with fracture modeling simulations to evaluate if a frac-job is over-stimulated. Stages that suggest over-stimulation are systematically analyzed and dynamic plots are presented, that compare the capital efficiency at different times during a frac job. Optimal completion designs that achieve uniform distribution of injected fluid volumes into multiple clusters are key to successful fracturing jobs. Simulations as well as field data show that if a large job volume is pumped with a sub-optimal completion design, fracture arrival at the offset well is early, leading to over-stimulation and wasted capital. In such a scenario, dominant clusters that take most of the injected fluid can intersect nearby offset well early in the treatment, while significantly bypassing undepleted reservoir rock along the lateral (that should ideally be drained) due to low cluster efficiency. This results in a frac job with poor capital efficiency and a well with lower productivity (due to interference with offset well). We show that early fracture arrival times are indicative of fewer clusters propagating fractures with very non-uniform fluid distribution (low cluster efficiency), whereas late arrival times indicate more uniform fluid distribution in the clusters with high cluster efficiency. We introduce a novel technique that analyzes field offset well pressure data and fracture arrival times at the offset well to diagnose stimulation efficiency and prevent over-stimulation. Our method provides operators with a relatively inexpensive way to improve capital efficiency during a frac-job.

Since 2010, hydrocarbon production from long horizontal wells targeting shales has become the norm for industry leaders. Because of the steep decline rates, it is vital to understand the reservoir and its properties before going through with a full-scale fracture stimulation. Through the application of Diagnostic Fracture Injection Tests (DFIT), one can determine accurate estimates of closure pressure, net pressure, pore pressure, formation permeability, and induced fracture geometry. The Utica shale is among the most promising reservoirs of the future, but there is limited information available discussing its properties. In SPE-196149-MS, we analyzed a DFIT from one horizontal well targeting the Utica. However, in order to fully understand the Utica shale at scale, further analysis is required. In this study, we will present three additional horizontal wells targeting the Utica, and analyze the pressure and its derivative to accurately estimate the properties mentioned above. DFIT analysis is an advanced technique to accurately predict stress regimes and reservoir properties. However, interpretation of DFIT data is challenging, especially in shale formations. In this study, we overview the geologic properties of the Utica shale, discuss the development of DFIT analysis and its governing equations, then present the three data sets and resulting conclusions. We specifically discuss the Tangent Line Method, the Compliance Method, and the Variable Compliance method in detail, while comparing their underlying equations and assumptions to determine closure pressure. After-Closure analysis is then performed in order to verify fracture closure and identify flow regimes. Through linear regression of this data, pore pressure from a linear flow regime is extrapolated, and through numerical simulation, key reservoir properties, such as permeability and fracture geometry, are estimated for the Utica shale. The DFIT interpretation and simulation results from this study are very insightful. Interpreting the GdP/dG function, the closure pressure ranges from 4,943 psi to 6,141 psi, contributing to a closure pressure gradient of 0.797 to 0.891 psi/ft for the Utica shale. Based on the pressure transient analysis, the pore pressure ranges from 3,238 psi to 4,064 psi, contributing to a pore pressure gradient of 0.486 to 0.616 psi/ft for the Utica shale. Additionally, field wide ranges of reservoirs properties are presented, allowing industry to further optimize their drilling and fracing techniques in the Utica shale. Two of the wells in this study are close in proximity and show very similar results both in After-Closure analysis and in pressure response curves. The third well displays a different GdP/dG response, leak off characteristics, pressure transient behaviors, formation permeability, and fracture geometry. This variance in results can be attributed to regional differences in geology, stresses, and pressures. Therefore, operators need to consider regional differences in reservoir properties in order to enhance the development of Utica shale and unlock all potential recoverable hydrocarbons.

This study demonstrates the application of an interpretable (or explainable) machine learning workflow using surface drilling data to identify fracable, brittle and productive rock intervals along horizontal laterals in the Marcellus shale. The results are supported by a thorough model-agnostic interpretation of the input-output relationships to make the model explainable to users. The methodology described here can easily be generalized to real-time processing of surface drilling data for optimal landing of laterals, placing of fracture stages, optimizing production and minimizing frac hits. In practice, this information is rarely available in real-time and requires tedious and time-consuming processing of logs (including image logs), core, microseismic data and fiber optic sensor data to provide post-job validation of frac- and well-placement. Post-completion analyses are generally too late for corrective action leading to wells with a low probability of success and increasing risk of frac hits. Our workflow involves identifying geomechanical facies from core- and well-log data. We verify that the geomechanical facies derived using core- and well-log data have characteristically different brittleness, fracability and production characteristics. We test and investigate several different supervised classifiers to relate surface drilling data to the geomechanical facies. The data was divided into training and test datasets, with supervised classification techniques being able to accurately predict the geomechanical facies with 75% accuracy on the test dataset. The clusters predicted on test well (unseen data) were qualitatively verified using the microseismic interpretation. The use of Shapley Additive Explanations (SHAP) helps explain the predictive models, rank the importance of various inputs in the prediction of the facies and provides both local and global sensitivities. Our study demonstrates that pre-existing natural fracture networks control both the hydraulic fracture geometry as wells as the production. Natural fractures promote the formation of complex fracture networks with shorter half-lengths which increase well productivity while minimizing frac hits and neighboring well interactions. The natural fracture network is itself controlled by the geomechanical properties of the rock. The ability of the surface drilling data to reliably predict the geomechanical rock facies provides a powerful tool for real-time optimization of wellbore trajectory and completions.

Mini frac, or diagnostic fracture injection test (DFIT), is a short hydraulic fracturing test that provides formation break-down pressure, minimum horizontal stress, and reliable value for formation permeability of shale reservoirs. The calculated formation permeability is particularly more reliable from the analysis of the second cycle of the mini frac test because the fracture is already created. In this paper, we present a simple technique to analyze and interpret DFIT data similar to the analysis of the classic drillstem test (DST) data in vertical wells. The only difference is that in DFIT pressure-time characteristics approximate the linear flow regime while in DST, pressure-time behavior follows the radial flow regime. In general, DFIT analysis provides matrix permeability while the analysis of long-term pressure decline of the production data yields stimulated formation permeability , which can be attributed to microfracture permeability . Thus, we will show how we utilize the permeability from DFIT, and the permeability calculated from the production decline data of production wells (i.e., multistage hydraulically fractured wells) to construct a viable dual-porosity model to assess the performance of wells under primary production and gas injection EOR . We also compare our results with those of Nolte G-function . The paper includes numerical modeling of two-phase nonlinear flow , analytical solution methodology from multi-phase flow, experimental data, and field data to illustrate the viability of our interpretation method. Furthermore, our analysis technique is simple because it only uses pressure falloff data points during the shut-in period of the DFIT. Not only the method is confirmed by numerical modeling , but it is also verified by pressure falloff from laboratory data.

Current experimental methods of assessing rock fracture toughness require a large sample size (i.e., Brazillian test, semi-circular bending, three-point bending), which cannot be extracted at greater depths and along horizontal well. Alternatively, fracture toughness can be evaluated at a finer scale using scratch testing. This study investigates the rock failure mechanism using micro-scratch testing and phase field modeling on rock fragments. The phase field approach models the crack growth and initiation based on energy minimization principles and by portraying the crack surface as a diffused entity. The method has been known for its robustness in preventing numerical singularities due to sharp crack discontinuities in complex crack topologies. In the phase-field scheme, a regularization scalar order parameter is used to indicate the material’s state (from undamaged to damage) during fracture formation. The associated loss of stiffness in rock during fracture formations is captured by the coupling of selected energy degradation function with embedded scalar order parameter and partial differential equations defining the deformation, history, and phase-field evolutions. In doing so, information on stress strain development is needed to evaluate the change in free energy during cracks formation. In this study, scratch testing is used to obtain load-displacement data related to stress strain history. During the test, an indenter scratches the surface of the rock under increasing load. The critical loads where the crack initiates and the chipping spallation occurs are identified based on the microscopic observations, acoustic emission signals, recorded tangential force and recorded depth. The critical loads are used to determine the crack length associated with chipping formation, while the recorded force displacement data are used to obtain the dimensionless stress-strain curve. Both the crack lengths and the dimensionless stress strain curve are then used as the input to the phase field model developed to approximate the fracture toughness of the rock tested. Scratch tests are performed on samples obtained from Eagle Ford formation. The experiments are conducted in short transverse and divider orientations. The crack formations are studied under the progressive load application. The critical loads where crack initiates and chips form are identified mainly based on the panoramic picture obtained after the test and the spikes seen on the Acoustic Emission signals. Preliminary results show that the fracture toughness is lower for samples tested in parallel to the bedding orientation (i.e., divider). Fracture toughness of rocks has attracted wide attention in the last few years in the design and analysis of hydraulic fracturing for hydrocarbon and geothermal recovery. The currently proposed methodology allows for a quicker and more reliable way of approximating rock fracture toughness from small rock samples. The incorporation of the phase field model allows better prediction of rock fracture toughness as the method is capable of overcoming classical model limitations of quantifying crack initiation and crack propagation in the complex fracture networks.

Numerical flow simulation models for CO 2 injection, transport and trapping mechanisms have been used to optimize geologic CO 2 storage (GCS) by improving trapping efficiency and injection strategies. Injection of CO 2 into geologic formations can cause geomechanical changes and lead to reservoir expansion, ground surface uplift, and induced seismicity. Such deformations create geomechanical risks associated with GCS, which can compromise the safety and storage capacity of CO 2 . The geomechanical risks of CO 2 sequestration have drawn significant attention in recent years due to considerable ground uplifting and induced microseismic activities that have been reported in several field cases. However, studies in this area have not considered the effect of geomechanical risks in optimizing the storage performance. We present an optimization framework to strategically place CO 2 injection wells to maximize the storage capacity and minimize the associated geomechanical risks. To this end, we perform the optimization using three-dimensional coupled flow and geomechanical models, by applying the Mohr-Coulomb plastic failure criterion to model mechanical rock failure risk. Additionally, the geomechanical simulation results are used to quantify the risk associated with ground surface displacement and plastic strain, which are extracted from the simulation outputs. A multi-objective optimization problem is formulated to maximize CO 2 storage while minimizing the two forms of geomechanical risks. The injection well locations are defined as decision variables and Genetic Algorithm is implemented to solve the multi-objective optimization problem. The solution of the proposed framework leads to nontrivial optimal decisions, which are different from the case where geomechanical risks associated with CO 2 injection are ignored. We find that the wells may not necessarily be concentrated in areas with the highest storage capacity because that may lead to rock failure and unacceptable levels of ground surface uplift. Instead, the maximum storage is limited to keep the reservoir in the elastic state based on the specified reservoir geomechanical and flow properties. We also observe that well interactions during CO 2 injection can cause shear failure of the formation between the wells. These observations suggest that accounting for geomechanical risks associated with CO 2 injection is necessary to design a sustainable plan for CO 2 injection and storage. The paper ends with a discussion about the importance of accounting for the uncertainty in rock properties and the resulting model predictions in optimizing the well locations.

While diagnostic fracture injection tests (DFIT) data is relatively rare, most hydraulic fracture treatment stages in multiple transverse fracture horizontal wells (MTFHWs) follow pressure and rate data during pumping with several minutes of pressure falloff data after the end of pumping. Recent papers have shown value in applying analysis developed for DFIT data to hydraulic fracture treatment falloff (HFTF) data. As is often the case with routinely acquired operational data, the time required for analyzing HFTF datasets for each of the treatment stages in a long horizontal well may be prohibitive. This paper offers an automated analysis procedure that starts from standard treatment pressure and rate data and produces estimates for wellbore and perforation friction loss, near wellbore tortuosity friction loss, and the instantaneous shut in pressure (ISIP). Steps in the automated procedure include isolating the HFTF data from the rest of the hydraulic fracture treatment data (which is typically subject to hydraulic hammer), applying an optimized low-pass filter (LPF), and computing the friction and ISIP estimates by automating a previously published graphic procedure. We employ the automated analysis on field data that was previously analyzed by hand. Then we compare and contrast between the two analyses. The comparison between manual and automatically analyzed fracture treatment falloffs demonstrates that the automated procedure reproduces the previous analyses except in a few cases that pose special challenges to any analysis. The new field dataset results demonstrate the approach is practical for field application. Variations in friction loss and ISIP estimates along MTFHWs provide data useful for well and pad completion design decisions related to perforating strategies, and fracture and well spacing.

This paper presents an optimum way to produce down to depletion a compartmentalized reservoir in offshore deep environment by considering geomechanical stress-deformation mechanisms and associated problems. The case study is for a faulted reservoir zone of the Aphrodite field, located in the Eastern Mediterranean. The study is based on finite element modelling using 2D plane strain analysis that incorporates pore pressure and elastoplastic deformation of reservoir and overburden rock formations using the Drucker-Prager plasticity model. The mechanical properties of the reservoir sandstones were derived from calibration of data obtained from triaxial tests and for the overburden shale layers from acoustic velocities and correlation functions. The compartmentalized geometry was constructed based on seismic data and logging data obtained at the exploration and appraisal phases. The estimated insitu stress field was transformed and applied on the boundaries of the model blocky geometry. Four different initial and equilibrium depletion scenarios were examined and the obtained results in terms of deformation and effective stresses are compared. The first scenario reflects the initial stress state, the next two intermediate scenarios present non-uniform depletion cases for each fault block, and the fourth scenario presents the case of a uniform depletion. It was found that the uniform depletion of the reservoir compartments creates the least stress contrast in the field and consequently, ensures better control of stress-related impacts during the production. The analysis highlights the local regions of a fault blocks system that potentially suffer by high shear strains that can cause fault reactivation or induced fractured zones but the over-all risk remains low. Furthermore, the analysis establishes relationships between the mean effective stress, volumetric strain, and permeability changes in order to predict the regions with improved transmissibility characteristics or the less permeable compacted rock regions of the reservoir. Overall, the analysis can provide an appreciation of the stress/strain-driven characteristics of the reservoir showing the area of rock compaction tendencies of the faulted blocks and the further deformation in depletion conditions. The presented work demonstrates clearly that a properly calibrated reservoir geomechanical model can be used as a screening tool for examining depletion scenarios of compartmentalized reservoirs, highlighting areas of potential problems such as fault activation, wellbore shearing, reservoir compaction, permeability changes and fault sealing.

The most common stimulation technique for shale production is multistage hydraulic fracturing. Estimating fracture geometry is a focal parameter to judge the fracture operation and predict the well performance. Different direct and indirect techniques can be used for fracture diagnostics to estimates fracture geometries. The current study combines fracture measurements and pressure transient analysis to estimate fracture surface area on each stage and to estimate production as a pseudo production log. The numbers and kinds of fractures were calculated as a function of treating pressures, injection rates, proppant concentrations, and formation properties to compute fracture surface area (FSA). Pressure transient analyses were then conducted with the leak-off data upon completion of each frac stage to estimate the producing surface (PSA). The fall-off data was processed first to remove the noise and water hammering effects. The PTA diagnostic plots were used to define the flow regime and the data were matched with an analytical model to calculate producing surface area. Tensile and shear fractures are both created during the injection of frac fluids. Shear fractures are caused by movement in already existing natural (fluid expulsion) fractures found in all shale source rocks. Shear fractures form a pressure below the minimum horizontal stress. These shear fractures take advantage of the rock fabric and develop higher surface area than tensile fractures for the same given volumes of water and sand. FSA is a measure of permeability enhanced area due to hydraulic fracturing. Producing surface area is the resulting effective flow areaconnected to the wellbore. Diagnostic plots showed a linear and radial flow regime depending on the formation and the completion design. Good correlations were found between PSA and FSA results. In general, higher FSA produces higher PSA. In cases where producing surface area was higher than expected from fracture surface area, communication was found with offset wells. When FSA higher than PSA were found, it was usually caused by increased stress from too close offset wells. Combining FSA and PSA measurements provides forecasts of production for each stage and helps to optimize well spacing at the end of each frac stage.

This study provides a systematic method to study the gas/water transport behavior and water retention behavior in gas shale reservoir using analytical and numerical modelling approaches. The critical water saturation determined from the relative permeability curve is regarded as the turning point between two gas production stages: Stage I and Stage II. At Stage I, the gas /water two phase flow dominates shale gas production period, while at Stage II the single gas flow and the flow of water in adsorbed phase are dominative. The improved permeability evolution model incorporates both the gas and water sorption-induced swelling strains. The permeability ratio is a time- and location-dependent parameter and its change can be divided into three stage, namely, the increase at early time, the decrease at mid-term time, and the increase at later production time. With gas depletion, gas pressure drawdown significantly dominates the evolution of permeability ratio. Continuously, the effect of sorption induced matrix shrinkage strain will become dominative with gas pressure decreases to low values. Due to the gas source supplement induced by gas desorption at Stage I, the gas production rate will temporarily increase but then will continuously decrease till to the lowest level at critical water saturation. At Stage II, the gas production rate is significantly influenced by residual water content in shale controlled by the flow of water in adsorbed phase. In addition, the effects of elastic properties ( i.e . Young's modulus and Poisson's ratio), initial permeability and diffusion time on permeability ratio and gas/water production profiles were discussed. These results provide a first rational method for analyzing the gas/water transport behavior and water retention behavior with potential application of shale gas recovery.

Recently new Distributed Acoustic Sensing (DAS) data have been collected during hydraulic fracturing in shale. Low frequency DAS signals show patterns that are intuitively consistent with the understanding of the strain field around hydraulic fractures. This study utilizes a fracture simulator combined with a finite element solver to further understand the various patterns of the strain field caused by hydraulic fracturing. The results can serve as a "type-curve" template for the further interpretation of cross well strain field plots. Incorporating detailed pump schedule and frac fluid/proppant properties, we use a hydraulic fracture simulator to generate fracture geometries, which are then passed to a finite element (FE) solver as boundary conditions for elastic-static calculation of the strain field. Since the FE calculated strain is a tensor, it needs to be projected along the monitoring well trajectory to be comparable with the fiber strain, which is uniaxial. Moreover, the calculated strain field is transformed into time domain using constant fracture propagation velocity. Strain rate is further derived from the simulated strain field using differentiation along fracture length. Scenarios including a single planar hydraulic fracture, a single fracture with a discrete fracture network (DFN), and multiple planar hydraulic fractures, in both vertical and horizontal directions were studied. The scenarios can be differentiated in the strain patterns based on the finite element simulation results. In general, there is a tensile heart shaped zone in front of the propagating fracture tip. On the sides there are compressional zones parallel to the fracture. Multiple planar fracture show polarity reversals in horizontal fiber due to interactions between fractures. Strain field/strain rate show consistent patterns with what is observed from field cross well strain data. The application of the study is to provide a template to better interpret hydraulic fracture characteristics using low frequency fiber strain monitoring. To the author's understanding, there are no comprehensive templates for engineers to understand the strain signals from cross well fiber monitoring. The results of this study will guide engineers toward better optimization of well spacing and frac design to minimize well interference and improve efficiency.

Well productivity reduction over time is one of the critical issues for deep-water wells with huge implications on expected recoveries from these wells. It is important to account for this uncertainty accurately in order to generate reliable production forecasts. Typically, reservoir simulation engineers utilize an expression (e.g. linear or exponential) for modeling changes in skin or Productivity Index (PI) over time as a function of either time or cumulative liquid production or pressure depletion. These commonly used single variable-based PI degradation modeling methods are easy to implement with a flow simulator, but they do not address the multi-dimensional nature of PI degradation which is a result of multiple subsurface effects combined with operational conditions. As a result, these single variable-based modeling methods generally do not have good reliability for predicting PI degradation trend. This article proposes a method for predicting reduction in producing well's PI by integrating a few key well operating variables (drawdown, borehole depletion, and water cut) into a single mathematical formulation. One of the important assumptions of IPDM is that certain critical drawdown pressure exists for each well in the field. When a well is operated below the critical drawdown pressure, negligible to no PI reduction is observed; however, when drawdown exceeds the critical drawdown value, noticeable PI reduction is seen. The reduction level depends on the ratio of current drawdown pressure to critical drawdown pressure, as well as on pressure depletion and water cut levels. By doing so, the global trend and local granularity of PI reduction are well captured. The concept of critical drawdown used in IPDM is aligned well with the awareness of safe drawdown among Reservoir Management practitioners. Critical drawdown ranges derived from IPDM form a useful analog data set while deciding safe drawdown limits or forecasting PI degradation trends for future wells. The predictability and generality of IPDM were assessed with historical well test (or PTA – Pressure Transient Analysis) data from more than 50 wells across seven deep-water fields. A detailed workflow of implementing IPDM was demonstrated through one of the field applications. From practical implementation point of view, IPDM method can be easily written in Excel Macro or using a PYTHON script or any other programming language. Once the methodology is coded (or implemented), it can then be plugged in a dynamic flow simulator (e.g. INTERSECT™). A similar approach is usually taken while incorporating single variable-based method for forecasting PI degradation into a flow simulator. Compared to the coupled modeling of geo-mechanical simulator - dynamic flow simulator, the IPDM is a much simpler approach to use and also enables engineers to evaluate the impact of key operating conditions on individual well's PI.

Diagnostic fracture injection tests (DFITs) have been widely studied and implemented in unconventional reservoirs to derive properties such as closure stress, pore pressure, and permeability. During a DFIT, a small volume of water is pumped into a formation to create a small-sized crack. Formation permeability is typically obtained by means of modeling fluid leakoff during the shut-in period. Early studies have assumed a constant fluid pressure boundary condition on the fracture walls or a constant leakoff rate into the formation. However, the results deduced based on these assumptions may introduce significant errors because the fluid pressure inside a fracture dissipates quickly as the fluid leaks off into the formation. In this study, we propose a material balance approach to obtain formation permeability using DFIT data. The proposed analysis takes into account fluid leakoff during both fracture propagation and well shut-in periods. To model fluid leakoff during fracture propagation, we adopt the superposition principle to decompose the problem into two separate problems; we then obtain the analytical solution. Two synthetic cases are presented to validate the proposed analysis. The results suggest that the proposed approach provides a good estimation of formation permeability. This approach has broad field application potential, as it can be used even when pressure data contains significant levels of noise. In addition, the solution is more accurate than those provided in available studies of formation permeability estimation using DFITs data, especially when formation permeability is not extremely tight.