Production history match can be used to evaluate effective fracture geometry and to confine the uncertainty of fracture and reservoir properties such as fracture conductivity and relative permeability. Although these parameters are critical in optimizing completions design such as well and cluster spacing, they are unfortunately difficult to be quantified using fracture modeling or most diagnostic techniques, which focus on geometry and properties during fracturing, different from those during production. To tackle this challenge, we leveraged the automatic history match (AHM) scheme based on Neural Network-Markov Chain Monte Carlo (NN-MCMC) to compare the parameters of a horizontal shale gas well with 74 days production history. 10 parameters characterizing the fracture and reservoir properties were quantified. The case with and without enhanced permeability area (EPA) were investigated. The posterior distributions of these parameters were obtained from the multiple history matching solutions. These multiple solutions were found by probabilistically iterating through 1 million realizations using the NN-MCMC algorithm and a total of 650 realizations were proposed to be validated with reservoir simulator. The MCMC algorithm has the advantage of quantifying uncertainty without bias or being trapped in local minima. The employment of neural network (NN) as a proxy model unlocks the limitation of an infeasible number of simulation runs required by a traditional MCMC algorithm. The proposed AHM workflow also utilized the benefits of Embedded Discrete Fracture Model (EDFM) to model fractures with a higher computational efficiency than a traditional local grid refinement (LGR) method and more accuracy than the continuum approach. We found that when EPA was included to represent small fractures surrounding main hydraulic fractures, the shorter fracture geometry posterior distributions were obtained compared with the case of hydraulic fractures only (without EPA). This causes the production forecast of the case with EPA to be significantly lower than the one with only hydraulic fractures (without EPA). This means that if a simple model with only hydraulic fractures was assumed while in the actual operation, there is EPA due to the small fracture networks created around main hydraulic fractures, we would overpredict the fracture geometry and gas EUR prediction. With the use of NN-MCMC as history matching workflow, the uncertainty range of 10 parameters were characterized automatically. These effective fracture geometry and properties can be used to improve well spacing and completion design in the next fracturing campaign.

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

Water flowback behaviors of unconventional gas reservoirs have been studied for gaining useful insights pertinent to fracture geometry characterization after fracturing stimulation. Field observations indicate that flowback profiles, such as fluid flow rates, flowback time, fracturing fluid recovery, may vary significantly among different wells. Stimulated fracture geometry has been widely postulated to be a dominant factor influencing flowback characteristics. This study attempts to identify the flowback signatures under various fracture geometries and configurations and to investigate effects of stimulated fracture geometry on flowback characteristics. In this study, an in-house three-dimensional coupled fluid flow and geomechanics simulator is used to simulate the flowback behaviors in unconventional gas reservoirs. The developed model incorporates essentially all the relevant physical mechanisms controlling flowback characteristics: capillarity, fracture closure, stress-dependent reservoir properties, and gravity segregation. Various complex fracture geometries are efficiently modeled through the Embedded Discrete Fracture Model (EDFM). Geomechanical deformations of the hydraulic and natural fractures are quantified based on widely-adopted fracture constitutive models. The flowback signatures under various fracture geometries are characterized by plotting different diagnostic plots. Fluid phase and pressure distributions are presented to help explain the mechanisms controlling observed characteristics. Two prominent regimes are observed for the whole flowback process: two-phase transient flow in fractures (early flowback period, EFP) and transient linear flow with considerable gas influx from matrix to fractures (late flowback period, LFP). Semi-log plots of water rate vs. cumulative water production (RVP) show near straight-line trends in EFP, and the slope of this straight-line increases as the total fracture volume increases. The curve moves left downward as the fracture interface increases under the same fracture volume. Complex fracture geometry leads to lower water recovery due to more water trapping in fractures. The existence of gas-filled natural fractures increases both the gas rate and ultimate water recovery, characterized by high gas water ratio (GWR) and a large slope in RVP plot during EFP. This study examines the salient signatures in flowback profiles for a variety of fracture geometries. The outcomes have offered new insights for the effect of fracture geometry on water flowback, facilitating the reduction in uncertainty of the stimulated fracture characterization using flowback data.

The Mississippian Osage and Meramecian Series have become important resource plays within the Oklahoma STACK in recent years. This study characterizes and models the dynamic performance of six (6) hydraulically fractured horizontal wells with staggered completions in Osage and Meramecian Series rocks to understand the origin of observed high water production volumes in the deeper wells. The study results allowed us to characterize a system of highly conductive fractures in the Osage and to devise a development plan that accommodates the unusual water transport behavior in this formation. A 3D static reservoir model was constructed for the northern part of Kingfisher County using abundant stratigraphic markers, high tier petrophysics and geomechanics data combined with a 3D seismic acoustic impedance inversion volume. A dual-porosity reservoir simulator with geomechanical features was utilized. This simulator dynamically simulates both fracture generation and dilation of existing fractures, as well as subsequent changes in stimulated reservoir volume geometry during production. The true injected volumes were simulated, allowing for characterization of the transport of injected water in the subsurface. The simulation model was calibrated to match the well performance during the hydraulic fracturing, flow back and depletion periods. Special attention was paid to the accurate modeling of water behavior in the six-well system, which motivated special modeling provisions to capture the presence of discrete high-conductivity fractures. A history matched simulation model that represents subsurface flow behavior and well performance for six adjacent horizontal hydraulically stimulated wells was generated for this study. The complex interactions of the existing natural fracture network with induced hydraulic fractures were characterized. The calibrated model showed that substantial quantities of water drained vertically downward, via natural highconductivity flow conduits, from shallower wells into deeper wells. Shallower wells thus exhibited dramatically superior oil production, while deeper wells acted primarily as water sumps, exhibiting nearly zero oil production with very high water production. These findings have various implications for the optimal development strategy in this region of the Mississippian carbonates. The geological and flow characterization of the Osage Series carbonates is novel as it explains anomalous water production rates and unusual levels of communication between nearby wells in this formation. The multi-well calibration of the simulation model provides physics-based justification for this mechanistic model of water transport. This understanding of large-scale conductive fractures in the Mississippian carbonates has important implications for operators in pattern development drilling, hydraulic fracture design and production cycles of field development in the STACK play.

Hydraulic fracturing, which is realized by injecting fluid and proppant materials with high pressure to open the formation, has been successfully employed for unconventional resource recovery for decades. During flowback and early-time production, the fracture closure may exhibit with a pressure drop of fracturing fluid dewatering and hydrocarbon withdrawal. This paper presented a model fully coupling flow and geomechanics for flowback and early-time production, which can comprehensively capture the dynamic behavior of fracture key parameters and optimize the strategies of resource development. In the coupled model, the control-volume method is used to numerically model fracture flow, with sufficient flexibility to consider geometries and conductivity distributions of propped and unpropped fractures. For the fracture geomechanics, the fracture aperture of unpropped fractures is characterized using the joint-closure relation. And the fracture conductivity is described using an empirical formula associated with effective normal stress and parameters of proppants for the propped fracture, which closes on the proppant. The discontinuous displacement method (DDM) is adopted to calculate fractures aperture and dynamically coupled with flow equations by updating of fracture parameters, with consideration of the matrix transient linear flow. The model is simple, but rigorous enough to consider the flow and geomechanics physics of the propped and unpropped fracture system. The ease of model setup and improved computational performance make it convenient for practical application. Detailed flow behavior analysis shows that the unpropped fractures, which are connected with the wellbore through propped fractures, experience a relative slow aperture throughout the closure process. And the fracture segments that open against lower normal stress have a larger initial aperture and faster aperture decline, compared to the segments that open against higher normal stress. The fractures key parameters, including the fracture permeability and fracture length are well interpreted by matching the field flowback and production data. Specially, the relationship between fracture conductivity and effective stress for both propped and unpropped fractures can be further correlated in a similar form with that of pressure-dependent fracture conductivity, which can be well used in the analytical, semi-analytical and fully numerical simulation models. The dynamic behavior of propped and unpropped fractures are investigated using a novel model, which fully couples fracture flow and stress with consideration of the fracture deformation. The new findings are also applied to the field data of a fractured shale gas well from the ChangNing shale in China. The results demonstrate the importance of accounting for dynamic behavior for deriving reservoir/fracture properties from flowback and early-time production data and for forecasting.

A large amount of fracturing fluid in fracking is imbibed into the shale fracture/matrix system, which leads to a significant uncertainty in gas recovery evaluation. The mechanism of imbibition impact on the gas–water two-phase flow is not well understood. In this study, systematic comparative experiments are carried out to simulate imbibition in fractured shale samples obtained from the Wufeng-Longmaxi Formation in China and the imbibition effect in the fracture–matrix system is qualitatively and quantitatively investigated. Nine shale samples are collected to measure their porosity and permeability using a helium porosimeter and nitrogen pulse–decay tests. Gas/liquid single-phase flow experiments are then carried out on three dry and saturated fractured samples using methane and KCl solution, respectively. Subsequently, dynamic imbibition experiments are carried out on three samples in a visualization container. The gas–water interfacial tension, water imbibition amount, and displacement velocity are recorded. A single-phase gas/liquid flow test shows a high linear correlation between the fluid displacement velocity and pressure gradient in the fractured samples as the fracture is the main flow channel, dominantly determining the flow behavior. Moreover, we introduce the capillary force in the cross flow term of the triple-medium model to characterize the imbibition effect, develop a two-phase flow simulation model of shale gas considering the fracturing fluid imbibition retention, and analyze the two-phase flow behavior by considering the imbibition effect of the fracturing fluid retention in the shale gas reservoir. The impacts of the fracturing fluid imbibition and complexity of the fracture system on the two-phase flow are still unclear. We propose systematic experiments to overcome this difficulty, which could provide valuable indicative information on the two-phase flow. Valuable experiment data are provided, which can be used to validate analytical equations for gas/water flow in the shale fracture–matrix system. 1. Introduction The steady domestic economic growth has led to an increase in demand for oil and gas. The conventional oil and gas resources cannot meet the high energy demand (Wang et al. 2020). The Chinese shale gas resources are widely distributed and have abundant reserves. The accumulated geological reserves of shale gas in the marine strata in the Sichuan Basin and its periphery are 764.3 × 10 9 m 3 (Zhang and Liu 2019). The shale reservoirs exhibit ultralow porosity and permeability (Du and Nojabaei 2019, Chai et al. 2019). In addition, the matrix permeability is generally of nD grade and the pore size is considerably smaller than those of sandstone (Javadpour et al. 2007). Various types of shale pores with multiple scales exist, including intragranular pores, microfractures, and fractures (Zou et al. 2013). The organic-rich shale has various hydrocarbon occurrences, mainly adsorbed gas and free gas, with a small amount of dissolved gas (Sheng et al. 2020). The above characteristics hinder the economic production from shale gas reservoirs (Yuan et al. 2015). The development of hydraulic fracturing technology in recent years has led to the developing value of shale gas considering the current oil price level (Zhou et al. 2015, Sheng et al. 2019).

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

Determination of well spacing and pad sequence are critical factors for maximizing production and yet remain challenging in unconventional plays. Data analysis of existing well performance provides an extensive knowledge base of ever changing designs, impact on performance and locations, however, integrated modeling has gained more attention despite the increase in time and effort. The scope of this paper is to illustrate a practical workflow alternative for rigorous multiple uncertainty analysis and optimization study that have been successfully applied to our unconventional reservoir factory-model development in the Permian Basin. Considering scenarios of multiple wells and pads with different sequences of completions and production, the workflow consists of three key phases. First, complex hydraulic fractures with a discrete naturally fractured network is modeled and converted to an unstructured reservoir simulation grid fitting simulator. The simulated well production performances then serve as a reference case. Second, the hydraulic fractures are further characterized by a logarithmic local grid refinement approach through an in-house reservoir simulation package designed for creating multiple realizations for history matching, uncertainty assessment, and optimization study, given reservoir heterogeneity and fracture variability. The whole section with different well spacing and pad sequence is then evaluated. Third, an in-house uncertainty analysis package is linked to both hydraulic fracture modeling and the in-house reservoir simulation platform for a variety of parameters including pad sequencing strategy/timing, well spacing, economic limit, matrix permeability, fluid type, and drawdown pressure. This workflow is fast and systematic while capturing the fracture geometry from complex hydraulic fracture modeling. Results from recent Midland Basin evaluations demonstrated that well interference should be considered at section level with all the wells to ensure proper section EUR consideration and different scenarios of pad sequences noticeably affect the section EUR, depending on the time differences, matrix permeability, fluid type and drawdown management. The novelty of this workflow is that 100s of realizations of different scenarios are created with the run time that is much faster yet results very similar to the more complex model’s result. Characteristics of Strategic Decisions in the Unconventional Strategic decisions for unconventional reservoir development have the following characteristics and are quite different with those in conventional reservoirs: Well Prioritization. There are many options to drill, complete and produce wells in an unconventional asset, given many sections with big areas and multiple vertical targets. The development sequence is laid out through overall economic prioritization.

Abstract Drilling multiple horizontal wells from a single pad has become a common approach in many shale plays in response to the economic, real estate, water management, regulations challenges the operators face while developing such plays. The challenge of optimizing the landing zones of those wells depends, in part, on the knowledge of the Stimulated Rock Volume (SRV) created during the fracturing jobs and the ability to predict its evolution during production. The objective of this work is to show how to get this understanding through a multidisciplinary workflow and how this helps to optimize a multi-landing zone development in a field case in Vaca Muerta. The first part of this work presents a sensitivity study in a single-well, focusing on the key geological and geomechanical factors with ranges based on data collected from well logs and field observations. These include characteristics of the natural fracture network, facies, laminations, variations on petroelastic properties and principal stresses, and anisotropy. The impact of these parameters upon the geometry of the SRV and well productivity is presented using pseudo-3D fracture model and fluid flow-geomechanics simulation coupling technique. Once the key parameters affecting SRV geometry and productivity are determined, the second part of this work shows the results of multi realization (multiple scenarios and well landings) on green and brown field stimulations. Analysis of the SRV geometry under undepleted and depleted conditions suggests that the stress change associated to production does impact the overall SRV generation and must be considered for multi-well multi-layer strategy. Horizontal Stress Anisotropy, preexisting fractures and laminations are the static properties which have the most important control on the Stimulate Rock Volume (SRV) dimensions and complexity. The SRV is dynamic, changes during time. Addressing these changes allows us to better plan a multi-landing zone design (sequence, landing depth, well spacing, etc.) at a given period of time for this field case. The presented work goes beyond an ordinary investigation of SRV creation driving properties: it allows for a better understanding of uncertainties related to these properties and ultimately depicts the static and dynamic impact on production in order to guide the optimization of well placement on the field case development.

Abstract The behavior of fractured low-permeability rock in many subsurface formations is critical for unconventional resource extraction. Understanding how flow through individual fractures changes during shearing, and what influence heterogeneity of the rock has on shearing behavior, was the focus of our laboratory study. Computed tomography (CT) scanning of fractured rocks undergoing shear was coupled with numerical simulations of fluid flow through these fractures. We sheared multiple cores from the Marcellus and Eau Claire shales in a closed system with confining pressures of greater than 1000 psi. Samples were manually sheared in a step wise fashion. After each shearing event we assessed the bulk hydrodynamic response by measuring permeability through the core and performed a high-resolution CT scan to understand how the principal and secondary fractures were changing in the core volume. The mineralogy of each sample was examined via x-ray fluorescence. A range of interdependent characteristics influence fracture network evolution and sample cohesion: mineralogy, lithological heterogeneity, principal fracture morphology, fracture asperities, and shearing direction in relation to bedding. We found that samples sheared parallel to bedding were less likely to develop extensive networks of secondary fractures, with secondary fracture growth contingent on the presence of large asperities. Fracture permeability tended to increase with continued shear and secondary fracture development, but a high variance existed between samples. In some instances, permeabilities decreased in response to shear-initiated aperture reduction due to fracture mating. Gouge formation is another factor contributing to the transmissivity decreases, particularly in shale-dominated fracture regions. The ability to study this complex behavior in a controlled fashion using CT scanning enables a view into processes that impact production in many unconventional formations. Findings show that small scale features and details can play a significant role in fracture behavior and should be accounted for. Introduction Shale properties vary significantly and understanding how fractures evolve due to geomechanical stressing can improve our understanding of how to effectively stimulate a variety of formations.While hydraulic fracturing is a large-scale activity, the microfabric and heterogeneity of shale can control fracture evolution and flow properties. Upscaling the impact of microfabric and heterogeneity is poorly captured in most modeling and planning efforts; this disconnect between small scale features and large-scale operations is understandable. It is difficult to measure changes in fractures directly, difficult to implement upscaled equations of value, and difficult to know if studied laboratory/outcrop samples are representative of activities in the subsurface. This study describes the observed behavior of two distinctly different shales under controlled geomechanical stressing to examine what impact small features have on fracture evolution. By examining two shales with distinctly different structure and composition our goal is to understand when inclusions of micro-features in upscaling is critical to understanding system dynamics.

We analyzed flowback (FB) and post-flowback (PFB) production data from six multi-fractured horizontal wells completed in Eagle Ford Formation. The wells are supercharged at the beginning of the flowback process and the reservoir pressure remains above bubble point during the post-flowback period. Interestingly, we observe a pronounced unit slope (pseudo-steady state) in the rate-normalized pressure (RNP) plots of water for post-flowback period, while such unit slope is not observed for the flowback period. We developed a conceptual and mathematical model to describe these observations and to estimate the average fracture pore volume (V f ) during the post-flowback process. This model assumes no water influx from matrix into the fracture system, which is consistent with the lack of mobile water in the target reservoir. It also assumes stable influx of oil from matrix into the fracture system with insignificant mass accumulation of oil in the fracture system. Therefore, water production at pseudo-steady state conditions occurs under the driving forces of water expansion, oil expansion, and fracture closure. We also performed decline curve analysis on water production data to estimate initial V f , as the fractures tend to be fully saturated with water at the beginning of the flowback process. The difference between ultimate water recovery and average V f from the PFB model represents the loss in fracture volume due to fracture closure. The results show that about 65% of fracture closure occurs after 7 months of PFB production. Fracture closure is the dominant drive mechanism during FB and early PFB periods when reservoir pressure drops rapidly. Introduction Analysis of flowback is becoming a common practice for early characterization of fractured horizontal wells completed in unconventional reservoirs. Several authors have developed different models for analyzing early flowback data to characterize complex fracture networks created by multi-fractured horizontal wells. Examples of recent studies include Abbasi et al. (2012, 2014), Ezulike et al. (2013), Clarkson and Williams-Kovacs (2013), Ezulike and Dehghanpour (2014a, b), Jia et al. (2015), Xu et al. (2016), Ezulike et al. (2016), Yang et al. (2016), Williams-Kovacs (2017) and Chen et al. (2017).

Abstract Production from naturally and hydraulically fractured reservoirs is highly dependent on the complex fracture geometry of the fracture network. It is computationally very expensive to model the mechanics, closure and flow of each individual fracture in a large domain with thousands of fractures. We propose a workflow to convert the discrete fracture network (DFN) of fractures into an effective permeability tensor that can be used to simulate flow in such complicated fracture networks. A discrete fracture network (DFN) of natural fractures is stochastically generated and the displacement discontinuity method based hydraulic fracturing simulator (Multi-Frac-NF) is used to model the hydraulic fracture propagation. This created fracture network along with induced unpropped (IU) fractures are imported into a geomechanical reservoir simulator. During flowback, the permeability tensor for the stimulated reservoir volume (SRV) is calculated. The effect of fracture height and natural fracture orientation on effective permeability tensor of SRV is systematically investigated. We show that the propagating hydraulic fracture can generate enough stress perturbations to allow hydraulically disconnected natural fractures to fail in its vicinity. These disconnected IU fractures can also increase the effective permeability of the reservoir close to the hydraulically connected fracture. Simulation results indicate that the effective permeability of the SRV is a strong function of the natural fracture orientation and hydraulic fracture height. We propose a workflow which includes the coupled effect of geomechanics and reservoir flow on the estimation of the effective permeability tensor for the SRV. The workflow presented in this paper provides a novel method to generate the reactivated natural fracture network around propagating hydraulic fractures and to capture the behavior of complex fracture networks in simplified reservoir simulation models using an effective permeability tensor for the SRV. Introduction In ultra-low permeability reservoirs, hydraulic fracturing stimulation is performed to maximize the surface area available for production of hydrocarbons. In the presence of natural fractures, hydraulic fracturing stimulation can create complex fracture networks (Fisher et al., 2002; Weng et al., 2011; Shrivastava et al., 2018b). Stress perturbations caused by hydraulic fracture propagation can lead to shear failure of natural fractures far away from the hydraulic fractures (Agrawal et al., 2019). These shear slippage events are registered as microseismic events. In the case of highly fractured reservoirs such as the Barnett a very complex pattern of microseismic events is observed (Fisher et al., 2002; Cipolla and Wallace, 2014). To capture the impact of this complex stimulation behavior on production and well performance in a simplified model, the concept of “Stimulated Reservoir Volume” (SRV) was introduced by Fisher et al., 2004. This has enabled traditional reservoir simulation models to use SRV as a proxy for complex fracture networks to mimic the actual production behavior observed in the field (Mayerhofer et al., 2010). However, often the SRV parameters are used as calibration parameters in history matching and are disassociated from the fracture modeling. This type of workflow can mimic the early production trends but can lead to erroneous predictions of well performance (Cipolla and Wallace, 2014).

Abstract Acoustic impedance tube and forced-oscillation seismic core test measurements were conducted to examine the low-frequency properties of acoustic metamaterial contrast agents. Water-stable suspensions of metal-organic framework (MOF) nanoparticles increased sound transmission loss (100-1250 Hz) and seismic attenuation (10-70 Hz), and reduced Young's modulus of nanofluid-saturated Berea Sandstone cores. Preliminary measurements were used to parameterize a seismic wave velocity model. These results indicate that injectable MOF nanofluid contrast agents have potential to enhance seismic delineation of subsurface fluids and structures. Introduction Subsurface monitoring of injected fluids and fracture networks is a critical component of geologic carbon storage and enhanced hydrocarbon recovery operations. Detection sensitivity, volumetric distribution, and migration paths of injectates are commonly difficult to obtain with geophysical techniques, especially in reservoirs containing complex secondary fracture networks (Figure 1) and/or extensive layering. Our goal is to develop a new class of seismic contrast agents to enable monitoring of injected fluids and gas-brine-hydrocarbon interfaces via conventional seismic imaging methods. We recently demonstrated that microporous metal-organic frameworks (MOF) are low-frequency (100-1250 Hz) absorptive acoustic metamaterials, exhibiting anomalous sound transmission loss and tunable resonance (Miller et al., 2018). Herein, we describe a novel class of injectable MOF nanofluid seismic contrast agents for enhanced mapping and monitoring of subsurface fluids and structures. We report increased low-frequency sound transmission loss due to water-stable MIL-101(Cr) (MIL: Materials Institute Lavoisier) nanoparticle suspensions and demonstrate that MIL-100(Fe) nanofluids influence the 10-70 Hz anelastic and elastic properties of saturated Berea Sandstone cores. These MOF nanofluid-based injectable contrast agents have the potential to comprise a disruptive high-performance geophysical technology for monitoring geologic CO 2 storage, oil and gas extraction, enhanced geothermal systems, and hydraulic fracturing. Materials and Methods Two MOF-based nanofluids were evaluated in this study. The two types of MOFs used in this study were chosen due to their similarity with previously-studied MOFs (Miller et al., 2018; Schaef et al., 2017) that exhibited notable low-frequency acoustic properties. The ~0.5 wt% nanofluids used in this study were prepared by synthesizing MIL-101(Cr) (Férey et al., 2005) nanoparticles [nanoMIL-101(Cr)] following previously-reported procedures (Schaef et al., 2017). NanoMIL-101(Cr) was selected for its very high specific surface area (SSA) of 2917 m 2 /g and its potential to form water-stable nanofluids (Nandasiri et al., 2016). MIL-100(Fe) (Horcajada et al., 2007) nanoparticles [nanoMIL-100(Fe)] were also synthesized for low-frequency property testing. MIL-100(Fe) nanoparticles were prepared using a similar method to that used for nanoMIL-101(Cr). Iron nitrate nonahydrate (0.5g, 1.23 mmol), 1,3,5-benzene tricarboxylic acid (0.174g, 0.83 mmol), and modulator 4-methoxy benzoic acid (9.4 mg, 0.62 mmol) were added to 40 mL of water. The heterogeneous suspension was mixed thoroughly followed by sonication for five minutes at room temperature. The mixture was then heated to 160 °C for 12 hours in a Teflon-lined autoclave. The reaction mixture was cooled to room temperature, isolated via centrifugation, and washed with deionized water and ethanol twice to produce a ~0.5 wt% nanofluid.

Abstract Natural fractures are a ubiquitous feature of unconventional reservoirs as evident from well logs, core studies, and micro-seismic interpretation. Hydraulic fracture (HF) generally intersects natural fractures (NF) leading to relatively complex geometry of the stimulated volume and the complications in proppant transport and deposition. In this paper, we simulate hydraulic fracturing in the presence of natural fractures in 3D and investigate key mechanisms in successfully stimulating and propping naturally fractured reservoirs. To our knowledge this if the first time the problem has been treated in 3D while considering HF/NF mechanical interaction. Several stimulations are considered using the state-of-the-art simulator “GeoFrac-3D” that can consider irregular fracture geometries and non-orthogonal intersection between the HF and NF, thereby realistic flow and proppant transport pathways and deposition sites. The “GeoFrac-3D” is based on the combination the displacement discontinuity method for the rock deformation, and the finite element method for the fracture fluid and proppant transport simulation. The deformation of the natural fractures is implemented using a linear joint model. The proppant transport and deposition within the fractures is modeled by treating the mixture of fluid and proppant particles as slurry. Example simulations are presented to explore the effective stimulation of fractured reservoirs using 100 mesh proppant. When the proppant can enter secondary fractures without extensive settling in the main HF, the propped surface area is maximized. Proppant settling velocities and thus proppant distribution is affected by fluid velocity, micro-proppant size, fluid rheology, fracture aperture, hydraulic and natural fracture interaction and near wellbore tortuosity. Introduction In hydraulic fracturing of unconventional reservoirs, the propagating hydraulic fracture (HF) generally intersects natural fractures (NF) complicating the geometry of the stimulated volume and the estimation of proppant flow and transport. The effectiveness of a hydraulic fracturing job depends on the resultant flow area and proppant pack permeability of the fracture system; therefore, a good understanding of the proppant transport and deposition is an essential component of hydraulic fracturing design. Several experimental studies (Sahai et al., 2014; Tong and Mohanty, 2016) and numerical studies (Weng et al., 2011; Tang et al., 2015; Han et al., 2016; Izadi et al., 2017) have been presented for the proppant transport and deposition in hydraulic and natural fractures (HF-NF) networks. These studies assume a stationary fracture network or a pre-defined propagation path. Recently, Kumar et al. (2019) presented a numerical study of the proppant transport and deposition in the HF-NF network and explored potential benefits of using of micro-proppant in the conductive fracture networks and demonstrated that due to induced stress shadowing effect near the intersections of the HF and NF's, the fracture openings are reduced which creates “choke or bottleneck points” as a resultant the bigger size proppants are prevented to enter into the natural fractures. In this paper, we have extended our earlier work to account for the potential propagation of the natural fracture wings and the impacts of NF's propagation on the proppant transport in the HF-NF networks. The objective is to explore and clarify the potential mechanisms involved in the successful stimulation of naturally fractured reservoirs with proppant deposition. We use the Eulerian-Eulerian approach to simulate proppant transport and deposition using a fully coupled 3D hydraulic fracture network model. We use “GeoFrac-3D” which can consider irregular fracture geometries and non-orthogonal intersection between the HF and NF, thereby capturing realistic flow and proppant transport pathways and deposition sites. A brief discussion of the mathematical formulations and numerical implementation are presented first, followed by several examples to illustrate some important phenomena in the proppant transport in the HF-NF networks in unconventional reservoir stimulation.

Simulating production from complex fracture networks is complicated due to different rates of closure of propped and unpropped fractures in a heterogenous time-varying stress field. Most of the existing models for simulating production from such hydraulic fractures do not consider geomechanics or use pressure as a proxy for changing the fracture conductivity. The closure of the unpropped fracture portion loses conductivity promptly, resulting in a fast decline rate in unconventional wells. However, most of the existing models are not capable of distinguishing the difference of propped and unpropped region in the fracture network. In this work, we developed a fully coupled, compositional, geomechanical fracturing and reservoir simulation model for simulating fracture propagation, proppant transport, proppant settling, flowback and fracture closure in complex fracture networks and applied this to field cases in the tight oil shale reservoirs. Our numerical model implicitly handles reservoir deformation and compositional multiphase fluid flow in rock matrix and propped/unpropped fractures. The simulation process consists of fracture creation during hydraulic fracturing and then modeling the shut-in and fracture closure followed by flowback over a period of several years. Total and effective stresses during production are calculated considering both pore pressure changes and mechanical opening of fractures. Closure of propped/unpropped fractures is modeled using an improved Barton-Bandis contact model. Previously published lab-measurements (Wu et al., 2017) for conductivity of propped and unpropped fractures as a function of effective stress are used as inputs for the closure model. The effects of proppant distribution, proppant size and different rates of fracture closure in propped and unpropped portions of the fracture are studied in using both planar fracture and complex fracture network. We show that the productivity of a fractured well is directly related to the proppant placement in the fractures. Achieving uniform proppant placement and reducing the proppant settling is beneficial in improving the fractured well productivity. This work will enable a better understanding of fracture closure during production, improving the accuracy of production forecasts and understanding inter-well interference.

Frac fluid delivery is selective in effect, so must fracture models. Here, a physics-based analytical model, called nine-grain model, is presented for production forecasting in multifrac horizontal wells in unconventional reservoirs, where the utilized formulation inherently enables defining three-dimensional non-uniform SRVs, selective frac-hits, and pressure- and time-dependent permeabilities. The model is validated by constructing case studies of liquid and gas reservoirs and comparing the results with numerical simulations. In cases with both production history and fracing-induced microseismic data available, the SRV's spatial structure is extracted using a hybrid four-level straight-line technique that links volumetric RTA estimations to morphometric microseismic analysis and entails plots of plasticity, diffusivity, flowing material balance and early linear flow. By applying our model to an oil well in Permian Basin, we demonstrate that the knowledge gained from the coupled microseismic-RTA contributes to resolving the non-uniqueness of RTA solutions. The proposed reservoir modeling procedure enables efficient incorporation of microseismic interpretations in modern RTA while honoring the SRV space-time variability, thus facilitates informed decision making in spacing design of wells and perforation clusters. Introduction Frac-hits. A frac-hit can be defined as observing a perturbation in the well production rate and/or pressure that is induced by a child offset (or an infill) well, usually triggered by pressure sinks created around parent wells or high permeability lithofacies. A frac-hit that temporarily alters the parent well productivity is called a communication frac-hit, and those with long-term effects, generally caused by fracture interference, are referred as interference frac-hits. A frac-hit may also compromise the productivity of the child well itself since the existing pressure sinks distribute the fracing energy in a larger area and might lead to an asymmetric fracture growth around the child well. Besides the parent well operational condition, the microseismic monitoring of fracing can potentially indicate interference frac-hits as it reveals fracture overlaps and any preferential fracture dilation towards existing wells. Depending on the rock and fluid properties, well age, parent-child horizontal and vertical distances, and the spatial extent of Stimulated Reservoir Volume (SRV), the constructive (Esquivel and Blasingame 2017) or destructive (King et al. 2017, Ajani and Kelkar 2012) effects of frac-hits can be experienced by fractures, SRV or the entire drainage volume (stimulated and non-stimulated zones), usually by impacting rock multiphase fluid interfacial arrangements and/or changing dimensions of conductive fractures. Aside from prevention, thoroughly reviewed by Whitfield et al. (2018), it is essential to incorporate frac-hits into production forecasting models, which to date, is not yet as straightforward as their detection. Both types of frac-hits cause a change in the well productivity over time which is not necessarily correlated with pressure, and hence, complicate the reservoir modeling process.

Abstract The capability to conduct a rapid, near real-time model-based analysis of production data from tight/shale (TS) gas fields is important in determining fracture and matrix properties. Model-based analysis of production can range from simple analytical solutions to complex numerical models. The objective of this study is to develop a simple, Excel-based tool for the analysis of the complex problem of gas production from a fractured TS gas reservoir that is based on a robust model that is faithful to the underlying physics and can provide rapid estimates of the important system parameters. The scientifically robust model used as the basis for this tool is a significant modification and expansion of the bimodal production decline curve of Silin and Kneafsey (2012). The production period is divided into two regimes: an early-time regime before the extent of the stimulated reservoir volume (SRV) is felt, where an analytical similarity solution for gas production rate is obtained, and a late-time regime where the rate can be approximated with an exponential decline or more accurately represented with a numerical integration. Our basic model follows Silin and Kneafsey (2012) and produces the widely observed -½ slope on a log-log plot of early-time production decline curves, while our expanded model generalizes this slope to – n , where 0 < n < 1, to represent non-ideal flow geometries. The expanded model was programmed into an Excel spreadsheet to develop an interactive, user-friendly application for curve matching of well production data to the bimodal curve, from which matrix and fracture properties can be extracted. This tool allows significant insight into the model parameters that control the reservoir behavior and production: the geometry of the hydraulically-induced fracture network, its flow and transport properties, and the optimal operational parameters. This information enables informed choices about future operations, and is valuable in several different ways: to estimate reserves and to predict future production, including expected ultimate recovery and the useful lifetime of the stage or the well; if curve-matching is unsuccessful, to indicate the inadequacy of the mathematical model and the need for more complex numerical model to analyze the system; to verify/validate numerical models, and to identify anomalous behavior or measurement errors in the data. The present approach can be adapted to gas-flow problems in dual-permeability media (hydraulically or naturally fractured) or highly heterogeneous sedimentary rock, as well as to retrograde condensation.

Abstract Discrete Fracture Networks (DFN's) incorporated into hydraulic fracture modeling and reservoir simulation are typically constructed and calibrated to all available high-quality natural fracture data from image logs and core, which generally results in an extremely limited calibration data set. To extrapolate these data over large areas, more broadly sampled data sets, such as discontinuity-related 3-D seismic attributes are often used. Broad spatial trending methodologies can potentially misrepresent natural fracture systems through over-reliance on seismic attributes that are commonly influenced by noise. The Hydraulic Fracture Test Site (HFTS) provides a rare insight of the subsurface natural fracture network and controlling factors on fracture distribution from a mechanical and lithological standpoint. The physical occurrence of hydraulic fractures and their interaction and relationship to preexisting natural fractures can be predicted using analytical models. Such model outputs can be applied to provide higher confidence when developing DFN's. Introduction The Hydraulic Fracture Test Site (HFTS) is located in Reagan County, TX (Figure 1). Understanding subsurface controls and operational impacts on natural and hydraulic fracture development is a primary objective of the HFTS and the focus of this paper. It should be noted that the analytical workflow described here utilizes measured rock parameters versus fluid and other engineering parameters which vary during the completion job. The HFTS operation involved drilling and completing 11 horizontal wells, recompleting 2 existing horizontal wells, and drilling a slant well to collect a low-angle core at 82 degrees inclination, drilled at a closest approach of 89' from an Upper Wolfcamp (UWC) well and 135' from a Middle Wolfcamp (MWC) well (Figure 2). Along with the slant core, an extensive well data set was collected, including open-hole logs, microseismic, cross-well seismic, pressure data, oil, water and proppant tracers, geochemical data (oil fingerprinting), and fiber coil production logs (Figure 3). The slant core fracture analysis consists of an integrated data set which makes up the fundamental calibration data for the analytical model discussed in this paper.

Abstract This paper presents methodologies to create simple reservoir models that reproduce the hydraulic behavior of complex networks of fractures in unconventional reservoirs. The methods use the results of the rate transient analysis (RTA) methodology recently developed by Acuña (2017). This approach shows that the Characteristic Flow Volume (CFV) is the fundamental property that defines fluid flow behavior for complex networks of fractures and that different reservoirs with the same CFV give the same hydraulic behavior. We use this premise to construct alternative models that we call butterfly models that share the same CFV of complex fracture systems but look different and are simpler to construct and simulate numerically while preserving the same hydraulic behavior. We also show how to construct and calibrate models based on the fractured models for each flow type proposed by Acuña et al. (2018). These fracture models offer a second alternative for construction of simple models. Comparison between the two types of simplified models is performed. Simulation work with the simplified fracture models is used to explain flow behavior commonly seen in unconventional wells without the need for enhanced permeability regions, compaction or desorption. This new approach has been validated with actual data and reservoir modeling and it can match not only the flow behavior of complex fracture networks but also has the capability to forecast the long-term performance. We also explore their use in multi-phase analysis and present a field case. Introduction Acuña et al. (2018) proposed fracture network configurations that explain the three types of behavior for unconventional wells: sub-linear, linear and sub-radial. Figure 1 shows these fracture models. Figure 1 (left) shows a schematic of a sub-linear flow fracture model where a complex network of highly conductivity fractures (purple and blue) creates matrix fragments of many different sizes. We have observed sub-linear flow in oil and in gas wells. Sublinear flow behavior is characterized by large initial production but large decline rate. For oil wells, the gas-oil ratio (GOR) sometimes increases to values several times the value for gas in solution and remains constant for a long time (Zhang and Ayala, 2015). When modeling sub-linear behavior with a linear flow model (Figure 1 center) we find that the calculated fracture length is not enough to deliver the initial production with the prevailing matrix permeability. This leads to the inclusion on enhanced permeability regions (Wang and Karaoulanis, 2016) next to the fractures to improve initial production. Matching the high decline rate, however, requires mechanisms such as stress-dependent permeability implemented in the form of compaction tables that may reduce fracture permeability up to 90% (Ali and Sheng, 2015) as the reservoir depletes. We demonstrate with simulation examples how sub-linear flow also results from the combined effect of matrix fragments of different size flowing together without compaction mechanisms or enhanced permeability regions. This fracture model is consistent with the observations in cores through the SRV by Raterman et al. (2017) and their statement that flow behavior is produced by fracture complexity alone and that matrix changes near the hydraulic fractures that may enhance permeability are extremely limited or absent. Acuña et al. (2018) add that reduction of fracture and matrix permeability with pressure depletion (compaction) should most of the time be a second order effect. The rock fracturing processes that may lead to this fracture network geometry are discussed in Acuña et al. (2018).

Abstract With an overwhelming attention drawn to unconventional resources recently, new challenges appear to be an unavoidable part of the business. These new challenges include fracturing efficiency and the presence of bypassed zones. The current paper discusses the possibility of monitoring the alteration of elastic properties of a low-permeability liquid shale reservoir over time (time-lapse) and implementing it as a means of identifying poorly fractured regions. This is achieved by performing petro-elastic and seismic forward modeling before and after a substantial volume of hydrocarbon has been produced from the reservoir. The fracture network is modeled with the corner point embedded discrete fracture model (cEDFM). Fracture density is altered in different locations, based on the efficiency of the fracturing jobs in those regions. With this model, shale matrix can be discretized using conventional orthogonal grid blocks, or corner point grids, for more complex formation geometry. Petro-elastic modeling results show that pressure depletion and gas evolution in the fractured zones can decrease the p-impedance by as much as 7%, which is greater than the minimum detectability threshold of the current seismic acquisition tools and processing techniques. Seismic forward modeling shows that hydrocarbon production and fluid substitution affect seismic amplitudes. The proposed method can provide an effective tool to identify poorly depleted and bypassed zones caused by an inefficient fracturing job. 1. Introduction With low permeability shale basins, deeper and more complex frontiers, and considerably low recovery factors, the importance of maximizing recovery from producing shale plays has never been greater. Hydrocarbon exploration, development, and production has experienced several game-changing technologies during recent decades, including the time-lapse, or 4D, seismic method. The basic premise of 4D is straightforward. The method involves acquiring, processing, and interpreting repeated seismic surveys over a producing field to understand reservoir changes over time, particularly during production. This understanding has real budgetary consequences because the increased recovery factor of a reservoir, even by a few percent, has significant revenue implications. The application of this technology in shale reservoirs is believed to help to alleviate the long-standing problem of poorly fractured (or bypassed) zones by periodically monitoring the elastic properties of the reservoir and identifying zones with minimal changes, which indicates the inaccessibility to those such regions. The major opportunity provided by 4D seismic data is its capability of imaging fluid flow in volumetric regions that are not sampled by wells (Lumley 2001). The role of shales as an active part of the reservoir and their sizeable effect on 4D seismic during the production lifetime will vary between geological scenarios and with reservoir sensitivity to changes in pressure and other properties (Rangel and MacBeth 2015).