Abstract Although scaling is common in both conventional and unconventional oil and gas wells, inflow scaling has not been studied in depth for unconventional environments. This paper presents a multi-disciplinary and nimble scientific approach proved to be effective in managing the discovery of scale in Point Pleasant wells in the Appalachian basin. The methodology included characterization of the scale (type/source identification, quantification and prediction) with development of methods for production surveillance and remediation. Utilizing a variety of solid sample testing, chemistry modeling, and investigative techniques, a strong basis of understanding was developed about the type, envelopes, and mechanisms of scale formation. Thermodynamic scale modeling coupled with tornado plots was used to identify key variables and then simplify into envelope plots for use in prediction and surveillance as input to key operational decisions. An in-house reservoir tool was developed as an adaptation of the Rose Plot, to quickly identify inflow impairment that is automated in a visualization tool and does not require bottom-hole pressure gauges. Remediation treatments with acid were applied to target both inflow and outflow regions of a well. Post-remediation production results from the squeeze treatments were within 200 Mscfd of the prediction for two of the treatment wells. The study confirmed scale existed in the lateral and possibly in the near-wellbore area (e.g. the perforations) of all three wells and proved an economical remediation technique for the inflow portion of a well, via 2 conveyance methods (tubing vs coil). Introduction Scale deposition in oil and gas wells is an age-old flow assurance problem in the Exploration & Production industry – where there are hydrocarbons and water there is likely to be scale (Morris, 1937). There are two primary types of scales - organic and inorganic. Organic scales are hydrocarbon-based and include deposits such as wax and asphaltenes. Inorganic scales are mineral deposits that can occur naturally based on produced water compositions, or when formation water mixes with different brines such as hydraulic frac water. The diversity of dissolved ions in formation water coupled with changes in the state of the reservoir fluids over time through production or addition of hydraulic frac fluids, may result in precipitation of carbonate, sulfate, sulfide and halite mineral scales (Rao, 2017).

Directional surveys are too far apart at the usual 90 feet in unconventional laterals. While it is considered uneconomic to survey at a closer spacing, an analysis of the positive displacement motor (PDM) slide/rotate sequences or rotary steerable system (RSS) set points along with standard MWD surveying can yield much higher fidelity in survey data. This paper covers the results of applying such a technique with the objective of delivering a less tortuous and more accurately placed lateral. Increasing the fidelity of directional surveys entails utilizing a statistical estimation-based forward tendency model. A PDM curve rate along with rotary build/drop and walk rates are balanced with the stationary surveys to capture the actual curve rates between the longer spaced surveys. A similar process is used when drilling with a RSS. This data allows for a better picture of the tortuosity within what will become hydraulic fracture stages which impacts frac development and performance. The data is also part of survey accuracy computations that now can be used to determine a more accurate placement or location of perf clusters or frac points within those stages. Examples of stage placement with and without high fidelity are shown. The accuracy of directional inclination, as used with 90 ft survey course lengths, is such that the true vertical depth error accumulated subsequent to the curve kick-off point is usually in the range of 30 ft or less in lateral sections. However, high fidelity analyses show that left/right spacing errors are larger than 100 ft between 20% and 40% of the time, depending on wellbore direction. This was not as significant in conventional directional wells. When unconventional laterals surround a new lateral at a 500ft spacing, this left/right error becomes as significant as TVD error. This problem becomes more acute as spacings become closer. The use of high fidelity techniques during drilling can lead to a balanced approach to PDM and rotary directional tendencies. This ability is not available without these real-time high fidelity computations. While this balancing is most pronounced with PDM’s, it is also possible with RSS’s. It will result in lower tortuosities, primarily in the laterals. Comparisons with hydraulic fracture data will detail the significance of this. Reducing wellbore tortuosity and improving lateral placement has an impact on the “drillability” of a well. This improvement along with the better knowledge of lateral curvature has a larger impact on completion design and the ability to centralize casing for cement isolation. Hydraulic fracture design can be modified for the different curve rates now visible in laterals. This higher precision in frac placement can be used in analyzing and preventing frac hits in nearby wells where high fidelity analysis has been performed.

The magnitude of elastic anisotropy in shale is a function of composition, texture, and fabric. Rock components such as mineralogy, organic content, clay mineral orientation, alignment of matrix pore and intraparticle kerogen pores, as well as the distribution of cracks, fractures, and other discontinuities can influence anisotropy. Elastic anisotropy has a significant impact on seismic waveform interpretation, time-depth models, and stress characterization used in drilling and well completion design. Anisotropy can be estimated explicitly from core measurements but the time and budgetary requirements to conduct extensive laboratory measurements are usually prohibitive in an operating environment. Existing models aimed at characterizing anisotropy from log data involve some assumptions that may not be realistic in every formation or lithology type. We aim to predict anisotropy from log data as a function of lithotype defined primarily by mineralogy, organic content, and porosity. This paper presents a workflow to identify lithotypes based on mineralogy, organic content, and porosity in core data from a single well and then predict elastic anisotropy for each lithotype away from the cored interval and in other wells. The workflow employs a multi-disciplinary experimental program using geology, engineering, and data analytics techniques to interpret data from core samples and log data obtained from a well in the Permian basin. First, we derive the relationship between stiffness anisotropy and lithotypes defined in core. Second, we derive the relationship between lithotype and electrofacies from log data using machine learning techniques like principal component and clustering algorithms. We then apply the predictive models to estimate anisotropy for each lithotype and test the predictive capability in the source well. Analyses of laboratory measurements reveal that anisotropy is not significantly influenced by any single mineralogical constituent, volume of organic material, or porosity. However, a multiple linear regression model that utilizes all three of those constituents measured from core is successful in predicting anisotropy for lithotypes identified from machine learning techniques. There is good agreement between measured and modeled anisotropy when applied as an upscaling tool using well log data. Further work will test the predictability of the model in a blind test well by comparing modeled results with core and log data that are independent of this analysis. This paper successfully applies a combination of traditional geological and engineering applications with new machine learning techniques to characterize lithotypes and predict rock properties such as elastic anisotropy. The technique avoids the assumptions used in existing models to characterize anisotropy and provides the foundational workflow that can be utilized to predict other rock properties for a variety of applications in the unconventional oilfield.

The total organic carbon (TOC) content in shale formations is one of the most important factors to identify hydrocarbon reservoir sweet spots and optimize production well placement, however, shale rock physics models are currently not well determined. Two methods have been used to estimate TOC volume from seismic data: 1) prestack amplitude variation with offset (AVO) inversion using the in-situ relationships among acoustic impedance (AI), shear impedance (SI), and TOC extracted from well logs; and 2) probabilistic neural networks applied to well logs and seismic attributes. Although these techniques are convenient to use, they are empirical and not strongly physics-based, so they may not be applicable in many cases. For this reason, we seek to find a more reliable and generalized TOC estimation method, which is better justified by rock physical relationships than existing methods. Our research objective is to develop AVO attributes to separately predict the TOC and lithology (in particular, clay volume fraction V clay ) from seismic data by using the exact Zoeppritz AVO equation. First, we conduct statistical analyses of three Wolfcamp well logs to derive relationships between seismic properties and shale rock properties. From these inferences, we build realistic shale rock physics models with realistic TOC (0–10%) and V clay (10–30%) values. Second, we design two-layer models with a carbonate layer, overlying the modeled Wolfcamp shale layers. We determine the seismic velocities and density of each modeled shale layer by using the statistical analyses. With these models, we conduct AVO modeling based on the Zoeppritz equation, generating AVO curves for the various reservoir shale scenarios. The full nonlinear Zoeppritz equation is more appropriate than linearized approximations because the latter are limited to weak impedance contrasts and weak anisotropy. The modeled AVO responses show that the seismic velocities are sensitive to V clay , and the bulk density is sensitive to TOC change. Moreover, we implement a sensitivity test for the A(intercept)-B(gradient)-C(curvature) terms of the AVO curves depending on the changes in the rock properties. We apply a least-squares curve fitting method to calculate the three (A, B, C) terms from the modeled reflection coefficients. Our results show that the C term can serve as a good lithology indicator because it is sensitive to V clay , not TOC, however, it is very difficult to estimate the C term accurately because it requires clean far-offset seismic data. We propose a new and more useful AVO attribute ‘D’ to detect the TOC change by the weighted sum of A and B terms. In contrast to the C term, the two (A, B) terms are often robustly estimated from near- and mid-offset seismic data. We conclude that our proposed seismic attribute D may provide a better method to estimate TOC from seismic AVO data and, thus, potentially discriminate it from Vclay for improved unconventional shale reservoir characterization.

Acoustic anisotropy and heterogeneity of unconventional formations with ultrasonic slowness and reflectivity images acquired with a newly developed logging-while-drilling (LWD) tool is studied. Conventionally, acoustic anisotropy has been evaluated with dipole or unipole sonic tools. However, if there is formation heterogeneity around the wellbore, what the dipole measurement can probe is the equivalent homogeneous mechanical properties. Unipole sonic tools can evaluate azimuthal heterogeneity and anisotropy. However, their ability to reveal fine formation features is largely limited due to spatial resolution limits of a few feet. The current study of using ultrasonic technologies is to overcome those limitations. The new LWD acoustic tool uniquely defines rock mechanical properties in inch scale as a function of azimuth in unconventional formations. The newly developed logging-while-drilling (LWD) ultrasonic tool is equipped with pitch-catch and pulseecho modules. It has been field tested in both vertical and horizontal wells. The pitch-catch measurement operates with a wide band ultrasonic frequency centered at 250 kHz, which enables the evaluation of formation mechanical properties at inch scale as a function of azimuth. The ultrasonic slowness log acquired with the new LWD tool is compared with the slowness log acquired with the conventional wireline dipole sonic tool run in the same well. Numerical modeling is also conducted to verify the novel ultrasonic pitchcatch measurements in the corresponding anisotropic formations. The field data reveals that the inch-scale ultrasonic slownesses image together with the ultrasonic reflectivity image logs can show characteristic features that clearly correlate to the formation lithology and structure. Those images also clearly show presence of heterogenous rock properties which cannot be evaluated with the standard sonic logging. In high gamma ray intervals, where the intrinsic transverse isotropy is expected, the vertical and the horizontal shear slowness with the ultrasonic pitch-catch measurements are different. Thus, the newly developed acoustic tool is effective to probe both the heterogeneity and anisotropy of unconventional formations while drilling. This work highlights the importance of evaluating acoustic anisotropy and heterogeneity of unconventional formations with high resolution slowness and reflectivity images. The formation mechanical properties around the wellbore in horizontal wells are not always homogenous, which is the common assumption in conventional sonic slowness analysis. Therefore, the target application of the current study with this new and unique LWD acoustic tool is completion optimization and geology and structure analysis with the detailed rock mechanical properties both in depth and azimuth.

This paper presents the results of modeling of two plug based measurement protocols: steady state, and unsteady state permeability measurements. The pulse decay measurement differs from steady state by the addition of a small volume reference chamber to the steady state apparatus and the consequent pressure boundary conditions applied. They are discussed in the context of both their strengths and weaknesses. The necessity of using the full nonlinear flow equation for the interpretation of the data is emphasized. Our implementation of the nonlinear gas flow equation includes assumptions of constant viscosity, constant rock compressibility, and pressure dependent permeability, i.e. the gas slippage effect (Klinkenberg corrections). Pressure dependent density effects increase the average pressure in the sample due to the nonlinear pressure profile induced. This leads to the estimation of permeability that is too small compared to an assumption of a linear profile. In contrast, the Klinkenberg effect results in increased flow and consequently an increased estimated permeability. It is therefore impossible to obtain unique values for the magnitudes of these effects from a single flow experiment. Multiple experiments at differing pore pressure resolves this problem through the use of a new analysis method the "k 0 -b" plot. From the results of the modeling, we believe that plug scale measurements are practical, and the standard GRI technique of grinding samples is not necessary. We recommend using plug based unsteady state measurements at multiple mean pore pressures to resolve gas slippage effects from intrinsic permeability effects. Introduction The most widely used technique to measure permeability in unconventional reservoirs involves grinding samples to between 500microns and 350 microns in size. A Boyle’s law experiment is then performed on the ground sample and the time dependent pressure data is interpreted for porosity and permeability. This reduction in sample size is performed in order to speed the measurement process from days to minutes. This grinding introduces several difficulties with the data interpretation. These include, among others, removal of large pores and smearing of clays in the ground material. Typically the interpretation of the data is based on extrapolating data measured on plugs at higher permeability (∼ one μD) to lower permeability and to the smaller sample size. This may involve extrapolation of the existing data as much as six orders of magnitude (measurements are often reported of less than a picoDarcy). To examine the possibility of making plug scale measurements and interpretation of measurement data we present the results of a full nonlinear modeling of plug scale measurements. We assume a constant grain compressibility and pressure independent viscosity. The assumption of constant grain compressibility is consistent with small changes in effective stress. A stress dependent rock compressibility may be included, but at the pressure gradients (100 psi) assumed it is assumed to be negligible. Viscosity is also assumed to be independent of pressure. For helium, nitrogen and methane, the viscosity varies by about one percent over this pressure range. We do not include inertial effects (Forchheimer terms) due to the low flow rates encountered in low permeability measurements. The general form of the nonlinear equation for single phase flow of gas in porous media is then given by:

Recent studies reveal that unconventional reservoirs contain complex natural fracture networks. Thus, in stimulating hydraulic fractures, it is important to study the interactions between natural fractures and hydraulic fractures. The goal of this work is to describe practical aspects of recent advances in the domain of geomechanical and discrete fracture network coupling, stimulation modeling, treating large number of fractures, adaptive mesh refinement methods, and overall fracture management within an unconventional setting. The computational framework is developed as an in-house code named IPACS (Integrated Phasefield Advanced Crack Propagation Simulator). Here, we describe a diffusive adaptive finite element phase field approach for modeling natural and hydraulic fractures. High fidelity finite element methods are employed to model multiphase flow with local mass conservation and dynamic mesh adaptivity. Geomechanics approximated by a continuous Galerkin finite element method is coupled to multiphase flow approximated by an enriched Galerkin finite element method by applying an iteratively coupled scheme. Introduction Through extended field experimentation recent field observations have shown that current stimulation models fall short in predicting hydraulic fracture geometries, proppant placement and transport, flowback, and the effects of stress shadowing and parent/child fracture parents. Moreover, most current simulators are unable to treat fracture propagation and production of flow and mechanics in a seamless fashion. Effects in including geochemistry are generally ignored except in very simple models. Thus, there is a need to demonstrate recent research efforts that can assist in predicting and modelling realistic stimulation processes. Consequently, engineering stimulated reservoir volume including proppant placement and/or acid fracturing treatments, can be achieved within computationally realistic frameworks, which can be used for reservoir management studies. In these research fields, the Center for Subsurface Modeling (CSM) in collaboration with other international institutes, has been contributing numerous studies. The emphasis has been on rigorous mathematical modeling, physics based discretizations, and numerical simulations. A robust and efficient computational framework for reservoir fracture modeling was developed resulting in IPACS - an integrated phase-field advanced crack propagation simulator. In this paper we describe and illustrate the main features of IPACS [1]. In this presentation we focus on a phase field approach for fracture stimulation. The phase-field methodology is a powerful tool for modeling the evolution of microstructures and their interactions of defects in a wide range of materials and physical models. The accurate simulation of fracture evolution in solids is a major challenge for computational algorithms, in large part due to crack paths that are generally unknown a priori. In this regard, phase-field approaches have shown great potential with their ability to automatically determine the direction of crack propagation through minimization of an energy functional. The phase-field framework naturally handles the emergence of phenomena such as crack nucleation and branching without the need to introduce additional criteria. In particular, formulations derived from variational theory have received a lot of attention from the applied mechanics community due to its strong ties to Griffith’s theory [2] for brittle fracture.

Many operators have increasingly moved toward cube development to avoid production impairment due to parent and child wells’ fracture-driven interactions (FDI). This cube development technique involves stimulating multiple wells in a section before bringing them online simultaneously or relatively close in time. This implies significant upfront investment to drill and complete in some cases 10’s of wells before producing a drop of hydrocarbon from them. Therefore, it becomes critical that the wells are completed optimally to be able to extract maximum resource from the reservoir. Multi-well stacked pad development renders itself as a 4D problem for completion optimization. Well spacing in horizontal and vertical direction and perforation spacing along the lateral being the 3 spatial dimensions, as well as the timing and sequencing of stages add the fourth dimension to the problem. Sensitizing for different sequencing scenarios in the modeling space before operational execution of the stimulation offers a cost-effective way to optimize production. We explore the impact of hydraulic fracturing sequence and spacing on production from the group of stacked wells in a section of the Delaware Basin. A three-dimensional geomodel along with a discrete fracture network is utilized to model a complex hydraulic fracture system created for multiple treatment sequencing and spacing scenarios. Stress shadow from previously stimulated stages is seen to be a major driver in controlling the geometry of the fractures in the wells stimulated later and can be utilized to enhance reservoir contact. Finite element modeling shows the positive impact of the stress re-orientation resulting from previously stimulated stages. Hydraulic fractures confined by stress from outside wells show clear growth pattern into unstimulated sections of the reservoir, thus enhancing the production potential. The stimulated reservoir volume and simulated production are used as key performance indicators (KPIs) for choosing the optimum sequencing and spacing strategy in this study, however the KPI can be changed to meet individual asset needs. This work aims to provide a workflow for modeling stacked well pad development and explores innovative approaches to sequence stimulation stages on wells in order to improve reservoir contact.

Frac-Hit is referred to the inter-well communication between the parent well (Offset well that is currently under production) and the Child well (the focal well that is being completed – Hydraulic Fractured). Today, traditional numerical reservoir simulation and modeling is used to model Frac-Hit. Overwhelming majority of operating companies simply use the distance between wells in order to address Frac-Hit. As the distance between the child well and the parent well is increased the probability of Frac-Hit between the wells may decrease. However, by increasing the distance between the wells (well spacing and stacking) the operating companies are reducing the recovery of the hydrocarbon from the shale formations. Conventional techniques (Rate Transient Analysis [RTA], Numerical Reservoir Simulation [NRS]) have proven not to have any serious contributions to the modeling and analysis of unconventional resources1. The large degree of assumptions and simplifications that form the foundations of these traditional technologies in their application to unconventional resources makes them unable to provide any reasonable contribution to analysis and modeling of Frac-Hit. Artificial Intelligence and Machine Learning is a purely fact-based predictive modeling technology that can address the current negative impact of Frac-Hit that has resulted in the reduction of the production and recovery of hydrocarbon from shale formations. Introduction Hydrocarbon production from shale plays is a function of the contact between the drilled wells and the shale reservoir due to tightness of the shale rock properties. The main reason that caused shale wells to be highly productive is inclusion of large number of hydraulic fracturing clusters that significantly increases the contact between the drilled wells and the shale reservoir. Another shale characteristic that significantly contributes to the increase of the contact between the drilled wells and the shale reservoir is the existence of the networks of natural fractures in the shale formations. Natural fracture networks significantly increase the expansion of the induced fracture into the shale formation. Nevertheless, existence of the system of natural fracture networks in the shale formations that has generated the possibility of significant increase in hydrocarbon production from shale wells has another characteristic that has lately been negatively impacting hydrocarbon production and recovery from shale wells. Frac-Hit is a function of the system of natural fracture networks in the shale formations.

Abstract In 2017, distributed acoustic sensing (DAS) technology was deployed in a horizontal well to conduct a time-lapse vertical seismic profiling (VSP) survey before and after each of 78 hydraulic fracturing stages. The goal of the survey was to more continuously monitor the evolution of stimulated rock throughout the treatment of the well. From two vibroseis source locations at the surface, time shifts of P-waves were observed along the well that decayed almost completely by the end of the treatment. A shadowing effect in the time shifts was observed that enables the height of the stimulated rock volume to be estimated. Using full wavefield modeling, the distribution of time shifts is well described by an equivalent medium model of vertical fractures that close as pressure declines due to fluid leak-off. Converted P to S waves were also observed to scatter off stimulated rock near some stages as confirmed with full wavefield modeling. The signal-to-noise ratio is a limitation of the current dataset, but recent improvements in DAS technology can enable stage-by-stage monitoring of the stimulated rock height, fracture compliance, and decay time as a well is completed. Introduction Distributed Acoustic Sensing (DAS) has opened new possibilities for seismic monitoring of unconventional reservoirs. Using a laser interrogator to launch light pulses down a fiber optic cable, dynamic strain changes can be sampled along the cable from the phase shift of light backscattered to the interrogator (Hartog, 2017). Since the fiber optic cable can be permanently cemented outside the casing in a borehole, highly repeatable vertical seismic profiling (VSP) surveys can be acquired frequently without costly wireline geophone deployments that interfere with well treatment activities (Mateeva et al., 2017; Meek et al., 2017). As described by Byerley et al., 2018, a unique interstage DAS VSP survey was conducted in 2017 during the stimulation of a horizontal well targeting the Wolfcamp formation in the Midland Basin, Texas. Using two vibroseis source locations offset about 1 mile from the heel and toe of the well, DAS data was acquired in the treatment well before and after each of 78 hydraulic fracturing stages. At the expense of fewer source locations, this type of acquisition allows the evolution of the stimulated rock volume (SRV) to be monitored on a stage-by-stage basis as the well is treated.

Abstract The objective of this study is to develop a workflow to rapidly simulate injection and production phases of hydraulically fractured shale wells by (a) incorporating fracture propagation in flow simulators using a simplified physical model for pressure-dependent fracture conductivity and fracture pore volume (b) developing a hybrid Fast Marching Method (FMM) and 3D Finite Difference(FD) model for efficient coupled simulation and (c) automating the entire workflow for rapid analysis in a single simulator domain. Pressure-dependent fracture transmissibility and pore volume multiplier models are assigned to predefined potential hydraulic fracture paths to mimic geomechanical behavior of fractures (i.e. opening and closure). The multipliers are based on empirical equations (e.g., Barton-Bandis model) and theoretical models (e.g., linear elastic fracture mechanics and cubic law). The FMM-based simulation transforms an original 3D reservoir model into an equivalent 1D simulation grid leading to orders of magnitude faster computation and is utilized to efficiently history-match field production and pressure data. A population-based history matching algorithm was used to minimize data misfit and quantify uncertainties in tuning parameters. We demonstrate the effectiveness and efficiency of the proposed method using synthetic and field examples. First, we validated our proposed simplified fracture propagation model with a comprehensive coupled fluid flow and geomechanical simulator, ABAQUS. The results showed close agreement in both injection pressure response and fracture geometry. Next, the method was applied to a field case to history-match injection pressure and production data. Fracture geometry and properties were inferred from the injection phase and are input to the production phase modeling. After history matching, the misfit and uncertainty ranges in reservoir and fracture properties were substantially reduced. The proposed workflow enables rapid analyses of hydraulically fractured wells and does not require computationally demanding geomechanical simulations to generate fracture geometry and properties. The FMM-based simulation further improves computational efficiency and allows us to automate the workflow using population-based history matching algorithms to quantify and assess parameter uncertainty.

Abstract Diagenesis encompasses many processes after deposition that are responsible for the dynamic evolution of the pore system. Understanding the role of diagenetic events on the connectivity and distribution of pores and migration pathways is vital for proper characterization of the rock. In this study, we critically examine diagenetic signatures in the Woodford Shale focusing on rock-fluid interactions that cause precipitation and dissolution and assess their impact on reservoir quality via multi-physics models. Evidence of diagenesis in shales have been extensively investigated by some of the authors in active and previous research. In this study, we focused on capturing the distribution of diagenetic features in the Woodford Shale using multiphysics models. Our methodology establishes a multi-disciplinary framework to incorporate multi-scale multi-physics data from various sources to investigate the impact of diagenesis on the alteration of petrophysical properties. Data incorporated include thin sections, scanning electron microscopy, and mineralogy. We first analyze and quantify the diagenetic signatures in the Woodford Shale. Examining the depositional history of the basin, mineralogy, the different pore types and the associated minerals. We then construct representative 3D pore-scale models and employ multi-component coupled fluid-flow and reactive-transport models to critically investigate these processes. Numerically, this entails concurrent solution of fluid-flow equations for pressures and fluxes, changes in fluid and mineral composition and conservation of solute mass for each component in the pore-network. We analyze porosity occlusion and the changes in migration pathways. This framework allowed us to determine the influence of chemical diagenesis (precipitation and dissolution) processes on the pore structure, connectivity, and fluid flow, in order to quantify the reservoir quality. Our initial pore-scale simulation effort yields promising results and is able to reproduce major diagenetic features. Future research efforts will include incorporating complex reactive kinetics and geomechanical stress-strain modules in the pore scale simulator that will enable us to examine more complex scenarios.

Abstract We employ microfluidics to capture the impact of several diagenetic processes, including the formation of vugs and fractures, cementation, and grain dissolution, on waterflooding sweep efficiency in diagenetically altered media. Heterogeneous porous media are constructed with glass micromodels using micro-CT images of sandstones in order to mimic chemical and mechanical diagenetic processes typically encountered in subsurface rocks. Cementation was emulated by placing micrograins in intergranular pores, dissolution was introduced by replacing stress-bearing grains with arrays of micrograins, a vug was incorporated into the pore system by removing grains from a circular area in the middle of the matrix domain, and a high-permeability channel was added to study the effect of a natural fracture on flow efficiency. From the five cases studied, we find porosity-forming processes such as those giving rise to vugs, natural fractures, and grain dissolution, result in the largest increases in recovery efficiency. Secondary pores enhance the merging of fingering dendrites, which results in higher recovery. In addition, the increase in local hydraulic conductivity due to porosity-forming diagenesis directs the fingering dendrites to traverse the middle of the matrix in addition to its boundaries. Modifying the geometry of micromodels according to probable burial stages (paragenesis), allows us to investigate the effect that subsurface conditions have on microscopic sweep and enables a quantitative interdisciplinary method for reducing reservoir development uncertainties. Introduction Pore-scale investigations can reveal dominant underlying fluid flow mechanisms for predicting the sweep efficiency of waterflooding in porous media. In pore-scale numerical modeling, the rock pore space is discretized via meshing or represented by an approximate pore-network depending on the domain size and available computational resources. Core-flood experiments are conducted by imposing a flow rate (or pressure gradient) on the porous medium and measuring the fluid volumes at the outlet. To evaluate microscopic sweep in core floods, pore-scale images of floods performed in small cores can be acquired using fast synchrotron imaging. However, both numerical modeling and core flooding become intractable in tight rocks1 due to resolution limitations for capturing the pore space in representative domain sizes (Bultreys et al., 2016). Microfluidics experiments have the unique ability to provide controlled environments for displacement experiments, including displacement of oil by waterflooding, in short time spans (minutes to hours). In addition, microfluidics devices allow direct visualization of flow and transport at the pore scale, which provides insight for engineering more effective recovery methods for subsequent experiments.

Abstract In this work we address the importance of numerical modeling for conducting sensitivity analysis of stacked, multi-stage, multi-well pad completions, as well as multi-pad completions, to optimize well placement and maximize well productivity. Designing stacked, multi-stage, multi-well, completions requires an evaluation of the induced stresses between interacting fractures and the effect that these stresses introduce into the growth of subsequent fractures. We tested the importance of the induced stressess by using two hydraulic fracture simulators that evaluate fracture geometry, propped surface area, and the local and far-field induced stresses at the end of the fracture treatment. Using a real case study in the Midland basin, we investigated the consequences of optimizing well placement to maximize well productivity using single-well simulations (i.e., assuming standalone wells), compared to conducting the same optimization using multi-well modeling (i.e., field zipper frac configuration). Results show that one cannot optimize the placement of stacked wells by treating them as standalone wells. We also investigated the effect of zipper fracture sequencing on the propped surface areas and well productivity. Results show that fracture sequencing affects the order of interaction between fractures and their associated induced stresses. In turn, this leads to changes in the fracture geometry and propped surface area, and thus influences the productivity of the entire pad or multi-pad system. The consequences of these changes are not easy to anticipate based on the knowledge of the individual well's behavior (either single stage modeling or multi-stage modeling). For the present case under investigation, after selecting the optimal wells placement, the propped surface area was practically insensitive to fracture sequencing. This, however, is not commonly the case. Furthermore, results showed a strong sensitivity to leakoff and the corresponding fracturing fluid efficiency. Unfortunately, this is not a parameter that can be controlled (except by using fluid loss additives and viscocifying agents). At the same time, this demonstrates the necessity of obtaining field leakoff measurements for accurate modeling.

Quantitative structural geology techniques can be used in conjunction with seismic data to define fault locations and geometry to reduce risk when planning horizontal wells. Unconventional plays in the past decade focus on basins characterized by largely horizontal stratigraphy and minimal faulting. However, even basins with minimal structure contain small-scale faults that pose unique risks to horizontal drilling. A fault with 100’ of throw or less can present well-bore stability issues due to natural fracturing and rock strength contrasts across faults. Seismic data can image these faults but because of their subdued nature, reliably interpreting their geometry and understanding the associated drilling risks can be difficult. We present case studies examining seismic sections from the Denver basin where horizontal wells intercept small-scale normal faults. These faults are visible on the seismic sections where they cut across the Niobrara at 30 – 45°. Wells that pass above, below, or intersect the faults at high angles are generally drilled and completed without issue. At deeper levels, wells intersected the same faults at very low angles (where fault dips < 30°) and experienced drilling and completion issues. The transition from steep fault dips within the Niobrara to low fault dips at deeper levels is not well resolved in the seismic sections but clearly represents a drilling hazard that should be considered. The geometry of the faults can be estimated using structural forward modeling and area-depth-strain (ADS) analysis. These established structural geology methods quantitatively relate seismically-imaged fold shape and horizon displacements to the underlying fault geometry. We use these methods to compute the deep fault geometry from the seismically observed folding of the Niobrara formation. We demonstrate that the wellbore collapse was related to fault angle and for a shorter lateral distance. This strongly suggests that the listric bends in these faults is a high-risk zone.

Barite scale formation in unconventional systems can severely reduce production rates and recovery. Barite in drilling mud (DM) is highly susceptible to dissolution (up to 20% of the total barite) when it interacts with a 15% hydrochloric acid spearhead leading to significant barite scaling as solution pH rises to circumneutral levels. In order to maintain the low pH spearhead that is favored by most operators, a new acid spearhead formulation was developed to stabilize the barite in place, closer to the borehole where open volume is large. This approach is dramatically different than typical scale mitigation practices in which precipitation from solution is targeted for control; but with unsatisfactory results. By using sulfuric acid instead of hydrochloric acid (equivalent acidity), the amount of Ba and SO 4 leached from DM was reduced by > 850-fold. This major reduction in barite dissolution translates into a significant reduction in the dispersal of these mineral-forming aqueous species in the hydraulically fractured shale matrix. As a result, reprecipitation of barite scale in the fracture network is minimized. Because some unconventional systems have high concentrations of calcite that dissolves upon interaction with the acid spearhead, gypsum can precipitate due to excess Ca 2+ derived from the calcite and its interaction with the additional SO 4 2− introduced from the new acid spearhead formulation. To mitigate this potential scale formation, Na-citrate was added to chelate Ca 2+ and inhibit gypsum formation. When only H 2 SO 4 was used, Na-citrate was not able to completely inhibit gypsum formation in high carbonate systems. However, by adjusting the H 2 SO 4 /HCl ratios and including Na-citrate, both barite and gypsum scale in the stimulated rock volume can be mitigated. These findings suggest that an incremental new best-practice is to stabilize the Ba/SO 4 in place rather than attempt to control precipitation from solution. Introduction Barite is one of the most important and problematic types of mineral scale in unconventional shale systems. Depending on the mineralogy of the deposit and solution pH, the amount and location of barite scale can differ (Figure 1). In systems where the generation of secondary porosity is minimal because of low concentrations of carbonate minerals, the precipitation of barite can reduce permeability by > 15% (Alalli et al., 2018). Efforts to mitigate barite precipitation focus primarily on either keeping barite nucleation from occurring or altering the surface properties of newly formed barite crystals to limit adhesion to shale and pipe surfaces (Antonious, 1996; Jones et al., 2003; Shen et al., 2009; Mavredaki et al., 2011; Yan et al., 2015; Bhandari et al., 2016; He and Vidic, 2016; Yan et al., 2017). These methods have limited success due to the intentional introduction of high quantities of barite in unconventional systems through drilling mud (DM). Previous work has shown that dissolution of barite in DM due to the injection of chemicals into the subsurface, primarily the 15% HCl acid spearhead, releases both Ba 2+ and SO 4 2− into the system that can precipitate as barite in fractures and shale matrices (Jew et al., 2018). On a per-mass basis, the barite released from the DM by the acid spearhead is significantly higher than that from the shale itself, indicating that the DM is most likely the dominant Ba/SO 4 source in these systems. Because of this underappreciated Ba/SO 4 source in unconventional systems, we developed a new model for barite in the subsurface (Figure 2). Because Ba and SO 4 are introduced into the system before stimulation fluid injection, any barite dissolved from the DM by the acid spearhead will be transported into stimulated rock volume (SRV) by the slickwater/slurry where precipitation will occur, necessitating a new approach to scale mitigation.

Abstract For conventional black oil reservoirs, oil production rate decreases rapidly as cumulative oil production increases under the condition of constant sand-face pressure. Normally, conventional decline curve analysis (DCA) is very good at predicting decline trend. However, after producing for a few years, decrease in oil production rate of unconventional reservoirs may be much slower than conventional black oil reservoirs. Actual production data of liquid-rich unconventional reservoirs (e.g., in Permian) also shows significant deviation from the typical decline curves. The traditional DCA cannot explain such abnormal behaviors of unconventional reservoirs. In this paper, a simulation-based DCA for unconventional volatile oil reservoirs is proposed to address the limitations of conventional DCA particularly in low GOR fluid type. First, data analytics is applied to select a representative well for dynamic modeling. Second, with input from fluid PVT, well-log, geology, and production data, a reservoir model for a well is built to simulate multi-phase flow behavior in the reservoir condition. As the subsurface uncertainty is very large, we applied multi-realization history matching to characterize the rock and geomechanical properties. Third, with all the combinations of subsurface parameters, we can simulate the full range of forecasting uncertainty and the rate decline trend. The results are analyzed carefully to understand if drive mechanism is primary phase depletion or secondary phase driven. The material balance approach is also used as a quality check procedure to make sure recovery factor is reasonable. The representative forecast curves are then used to derive a new formulation of DCA. Results of numerical simulations are consistent with both theoretical analysis and actual production data, which further validates the new formulation of DCA for unconventional reservoirs proposed in this paper. We observed one case where oil rate declines to a plateau for an extended time. This phenomenon could be explained by solution-gas drive and captured by simulation model. The proposed method considers physics and real production data, and hence it is very useful when conventional DCA fails to predict the trend. For example, when reservoir pressure decreases below bubble point, solution gas comes out and traps in the matrix when gas saturation is smaller than the critical gas saturation. Solution gas is now a big player in driving the production. Physics-based simulation can capture oil rate decline due to solution gas driven mechanism, which normally happens later in the producing life of a well.

Abstract The goal of our work was to maximize gas production and recovery from a horizontal appraisal well in the Mancos shale in New Mexico. This required a fracture design that would maximize perforation cluster efficiency and a lateral placement strategy that would maximize gas recovery. A key challenge was to design a fracture treatment that would overcome the extreme stress shadowing effects. Another key challenge was to optimize the lateral placement balancing multiple factors. Fracture treatment simulations were completed for various designs. Fracture simulations indicated cluster efficiency could be dramatically improved by optimizing the way we pump the pad. A step-up technique for increasing pumping rates during the pad stage helped to initiate more fractures. Intra-stage diversion was utilized. Fracture simulations were performed to optimize the lateral placement. This required balancing multiple factors to access the highest gas-in-place (GIP) interval yet facilitate more fracture initiations per stage. Fracture descriptions from the fracture simulations were input to a reservoir simulator to determine the optimal design. This paper will focus on the hydraulic fracture modeling. This appraisal well was the most productive Mancos gas well ever delivered in the San Juan Basin. The 9,546’ lateral produced at a choke constrained plateau rate of about 13 MMscfd for 7 months and produced over 6 BCF in the first 20 months. A radioactive tracer log indicated an overall perforation cluster efficiency of 83%, a significant achievement in a shale with high stress shadowing. The fracturing fluid design, diverter design and pumping techniques can be applied in many other shales as a low-cost way to increase perforation cluster efficiency, which will in turn result in higher production rates and higher cumulative recovery. Building on the success observed in the Mancos wells, BP and BPX Energy have subsequently utilized these techniques in other shale plays with success. The concepts and workflow used to decide the optimal lateral placement is a well-defined approach that can be applied to other unconventional wells to increase hydrocarbon recovery.

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.

Abstract Tightly spaced horizontal wells are widely used in the development of unconventional resources. The effectiveness of this strategy is largely affected by interwell fracturing interference indicated by interwell fracture geometry and frac hits, as interwell interference affects both parent and infill well productions. This work proposes a reservoir-geomechanics-fracturing modeling workflow for understanding the interference mechanism and quantifying effects of parent well fracture geometry, differential stress, and the design of infill well completion on interwell fracturing interference. Reservoir models are constructed for the analysis of Eagle Ford scenarios. The numerical workflow involves a finite element model that fully couples reservoir flow and geomechanics and a complex multi-fracture propagation model coupling rock mechanics and fluid flow in wellbore and fractures. The workflow characterizes the temporal-spatial evolution of pressure and stress caused by legacy parent well production. The fracture model is employed to simulate the complex fracture geometry created by infill well completion based on updated heterogeneous reservoir stress state. The resulting fracture geometry quality is quantified by the occurrence of frac hits and the relative growth of fractures in longitudinal and transverse directions. Non-uniform fracture geometries lead to more complex stress change induced by depletion than uniform fracture geometries along parent wells. A smaller in-situ differential stress results in stronger stress reorientation caused by parent well depletion, which induces longitudinal fractures along infill wells and greatly reduces stimulated reservoir volume and initial well performance of infill wells. A larger in-situ differential stress induces less stress reorientation and is more likely to lead the fractures propagating toward pre-existing fractures, generate frac hits, and affect the production of parent wells. The quantification study in the sensitivity analysis indicates that differential stress and the infill well completion design have the most significant influences on interwell interference. This study suggests optimum infill well completion designs for Eagle Ford scenarios. The study also provides insights for infill well completion design in unconventional reservoirs developed by tightly spaced horizontal wells in terms of how to adjust field operational schedules to avoid frac hits and change the complexity of the interwell fracture networks.