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Abstract This paper presents a continuum-scale diffusion-based model informed by pore-scale data for gas transport in organic nanoporous media. A mass transfer and adsorption model is developed by considering multiple transport and storage mechanisms, including bulk diffusion and Knudsen diffusion for free phase, surface diffusion for sorbed phase, and multilayer adsorption. The continuum-scale diffusion-based governing equation is developed solely based on free phase concentration for the overall mass conservation of free and sorbed phases, carrying a newly-defined effective diffusion coefficient and a capacity factor to account for multilayer adsorption. Diffusion of free and sorbed phases is coupled through the pore-scale simplified local density method based on the modified Peng-Robinson equation of state for confinement effects. The model is first utilized to analyze pore-scale adsorption data from the krypton (Kr) gas adsorption experiment on graphite. Then we implement the model to conduct sensitivity analysis for the effects of pore size on gas transport for Kr-graphite and methane-coal systems. The model is finally used to study Kr diffusion profiles through a coal matrix obtained through X-ray micro-CT imaging. The results show that the sorbed phase occupies most of the pore space in organic nanoporous media due to multilayer adsorption, and surface diffusion contributes significantly to the total mass flux. Therefore, neglecting the volume of sorbed phase and surface diffusion in organic nanoporous rocks may result in considerable errors. Furthermore, the results reveal that implementing a Langmuir-based model may be erroneous for an organic-rich reservoir with nanopores during the early depletion period when the reservoir pressure is high.
Abstract Defined by SPE as the application of basic and engineering sciences to the finding, development, and recovery of oil, gas and other resources from wells, petroleum engineering (PE) has been throughout the years falsely thought of as an amalgamation of other disciplines applied to the exploration and recovery of hydrocarbons. Integrating all PE subdisciplines in a manner efficient for teaching and learning is essential for securing the abundance of well-rounded market-attractive professionals. This paper discusses advantages individuals with PE background experience should exhibit in their employment in the oil and gas industry and academia. There is no point for students in going to school for a degree that will not hand them a competitive edge within their discipline. For graduate PEs, the job market is dependent on the quality of their respective academic programs and by extension to the quality of the teaching faculty. A steady oil and gas job market may not necessarily warrant robust employment opportunities, particularly straight after graduation. In a discipline like PE, where almost everything that matters takes place thousands of feet underground, apportioning credit for successes or responsibility for failures is itself a challenge. Decreases in student enrollments in PE programs reported by various universities during times of low oil and gas prices poses questions about the future of the PEs discipline, despite the steady demand for oil and gas in the world's energy mix. Academic programs interested in facilitating a smooth transition of their graduates into the industry should work in conjunction with practitioners to provide the correct balance between theory and practice in their coursework ensuring that once employment opportunities are created, they get filled with candidates of relevant education and training. PE degree-holding candidates should be the natural first choice for PE positions. This means that their educational and professional backgrounds should be providing them with an undisputed advantage which places them a leg above candidates from other disciplines. For instance, for a well completions job opening, there should not be a better alternative than a good PE specialized in well completions. If every PE graduate comes out of his or her program with a skillset which is superior to that of his or her competition, he or she will be the preferred choice for an oil and gas job.
Abstract The Tuscaloosa Marine Shale (TMS) formation is a clay- and liquid-rich emerging shale play across central Louisiana and southwest Mississippi with recoverable resources of 1.5 billion barrels of oil and 4.6 trillion cubic feet of gas. The formation poses numerous challenges due to its high average clay content (50 wt%) and rapidly changing mineralogy, making the selection of fracturing candidates a difficult task. While brittleness plays an important role in screening potential intervals for hydraulic fracturing, typical brittleness estimation methods require the use of geomechanical and mineralogical properties from costly laboratory tests. Machine Learning (ML) can be employed to generate synthetic brittleness logs and therefore, may serve as an inexpensive and fast alternative to the current techniques. In this paper, we propose the use of machine learning to predict the brittleness index of Tuscaloosa Marine Shale from conventional well logs. We trained ML models on a dataset containing conventional and brittleness index logs from 8 wells. The latter were estimated either from geomechanical logs or log-derived mineralogy. Moreover, to ensure mechanical data reliability, dynamic-to-static conversion ratios were applied to Young's modulus and Poisson's ratio. The predictor features included neutron porosity, density and compressional slowness logs to account for the petrophysical and mineralogical character of TMS. The brittleness index was predicted using algorithms such as Linear, Ridge and Lasso Regression, K-Nearest Neighbors, Support Vector Machine (SVM), Decision Tree, Random Forest, AdaBoost and Gradient Boosting. Models were shortlisted based on the Root Mean Square Error (RMSE) value and fine-tuned using the Grid Search method with a specific set of hyperparameters for each model. Overall, Gradient Boosting and Random Forest outperformed other algorithms and showed an average error reduction of 5 %, a normalized RMSE of 0.06 and a R-squared value of 0.89. The Gradient Boosting was chosen to evaluate the test set and successfully predicted the brittleness index with a normalized RMSE of 0.07 and R-squared value of 0.83. This paper presents the practical use of machine learning to evaluate brittleness in a cost and time effective manner and can further provide valuable insights into the optimization of completion in TMS. The proposed ML model can be used as a tool for initial screening of fracturing candidates and selection of fracturing intervals in other clay-rich and heterogeneous shale formations.
Summary A novel multiphysics multiscale multiporosity shale gas transport (MST) model was developed to investigate shale gas transport in both transient and steady states. The microscale model component contains a kerogen domain and an inorganic matrix domain, and each domain has its own geomechanical and gas transport properties. Permeabilities of various shale cores were measured in the laboratory using a pulse decay permeameter (PDP) with different pore pressure and confining stress combinations. The PDP-measured apparent permeability as a function of pore pressure under two effective stresses was fitted using the microscale MST model component based on nonlinear least squares fitting (NLSF), and the fitted model parameters were able to provide accurate model predictions for another effective stress. The parameters and petrophysical properties determined in the steady state were then used in the transient-state,continuum-scale MST model component, which performed history matching of the evolutions of the upstream and downstream gas pressures. In addition, a double-exponential empirical model was developed as a powerful alternative to the MST model to fit laboratory-measured apparent permeability under various effective stresses and pore pressures. The developed MST model and the research findings in this study provided critical insights into the role of the multiphysics mechanisms, including geomechanics, fluid dynamics and transport, and the Klinkenberg effect on shale gas transport across different spatial scales in both steady and transient states.
Pei, Yanli (University of Texas at Austin (Corresponding author) | Yu, Wei (email: email@example.com)) | Sepehrnoori, Kamy (University of Texas at Austin and Sim Tech LLC) | Gong, Yiwen (University of Texas at Austin) | Xie, Hongbing (Sim Tech LLC and Ohio State University) | Wu, Kan (Sim Tech LLC)
Summary The extensive depletion of the development target triggers the demand for infill drilling in the upside target of multilayer unconventional reservoirs. However, such an infill scheme in the field practice still heavily relies on empirical knowledge or pressure responses, and the geomechanics consequences have not been fully understood. An embedded discrete fracture model (EDFM) is deployed in our fluid-flow simulation to characterize complex fractures, and the stress-dependent matrix permeability and fracture conductivity are included through the compaction/dilation option. After calibrating reservoir and fracture properties by history matching of an actual well in the development target (i.e., third Bone Spring), we run the finite element method (FEM)-based geomechanics simulation to model the 3D stress state evolution. Then a displacement discontinuity method (DDM) hydraulic fracture model is applied to simulate the multicluster fracture propagation under an updated heterogeneous stress field in the upside target (i.e., second Bone Spring). Numerical results indicate that stress field redistribution associated with parent-well production indeed vertically propagates to the upside target. The extent of stress reorientation at the infill location mainly depends on the parent-child horizontal offset, whereas the stress depletion is under the combined impact of horizontal offset, vertical offset, and infill time. A smaller parent-child horizontal offset aggravates the overlap of the stimulated reservoir volume (SRV), resulting in more substantial interwell interference and less desirable oil and gas production. The same trend is observed by varying the parent-child vertical offset. Moreover, the efficacy of an infill operation at an earlier time is less affected by parent-well depletion because of the less-disturbed stress state. The candidate infill-well locations at various infill timings are suggested based on the parent-well and child-well production cosimulation. The conclusions provide practical guidelines for the subsequent development in the Permian Basin.
Summary Stimulated reservoir volume (SRV) is a prime factor controlling well performance in unconventional shale plays. In general, SRV describes the extent of connected conductive fracture networks within the formation. Being a pre-existing weak interface, natural fractures (NFs) are the preferred failure paths. Therefore, the interaction of hydraulic fractures (HFs) and NFs is fundamental to fracture growth in a formation. Field observations of induced fracture systems have suggested complex failure zones occurring in the vicinity of HFs, which makes characterizing the SRV a significant challenge. Thus, this work uses a broad range of subsurface conditions to investigate the near-tip processes and to rank their influences on HF-NF interaction. In this study, a 2D analytical workflow is presented that delineates the potential slip zone (PSZ) induced by a HF. The explicit description of failure modes in the near-tip region explains possible mechanisms of fracture complexity observed in the field. The parametric analysis shows varying influences of HF-NF relative angle, stress state, net pressure, frictional coefficient, and HF length to the NF slip. This work analytically proves that an NF at a 30 ± 5° relative angle to an HF has the highest potential to be reactivated, which dominantly depends on the frictional coefficient of the interface. The spatial extension of the PSZ normal to the HF converges as the fracture propagates away and exhibits asymmetry depending on the relative angle. Then a machine-learning (ML) model [random forest (RF) regression] is built to replicate the physics-based model and statistically investigate parametric influences on NF slips. The ML model finds statistical significance of the predicting features in the order of relative angle between HF and NF, fracture gradient, frictional coefficient of the NF, overpressure index, stress differential, formation depth, and net pressure. The ML result is compared with sensitivity analysis and provides a new perspective on HF-NF interaction using statistical measures. The importance of formation depth on HF-NF interaction is stressed in both the physics-based and data-driven models, thus providing insight for field development of stacked resource plays. The proposed concept of PSZ can be used to measure and compare the intensity of HF-NF interactions at various geological settings.
Summary We propose a novel method for estimating average fracture compressibility during flowback process and apply it to flowback data from 10 multifractured horizontal wells completed in Woodford (WF) and Meramec (MM) formations. We conduct complementary diagnostic flow-regime analyses and calculate by combining a flowing-material-balance (FMB) equation with pressure-normalized-rate (PNR)-decline analysis. Flowback data of these wells show up to 2 weeks of single-phase water production followed by hydrocarbon breakthrough. Plots of water-rate-normalized pressure and its derivative show pronounced unit slopes, suggesting boundary-dominated flow (BDF) of water in fractures during single-phase flow. Water PNR decline curves follow a harmonic trend during single-phase- and multiphase-flow periods. Ultimate water production from the forecasted harmonic trend gives an estimate of initial fracture volume. The estimates for these wells are verified by comparing them with the ones from the Aguilera (1999) type curves for natural fractures and experimental data. The results show that our estimates (4 to 22×10psi) are close to the lower limit of the values estimated by previous studies, which can be explained by the presence of proppants in hydraulic fractures.
Peng, Sheng (University of Texas at Austin (Corresponding author) | Shevchenko, Pavel (email: firstname.lastname@example.org)) | Periwal, Priyanka (Argonne National Laboratory) | Reed, Robert M. (University of Texas at Austin)
Summary Water-oil displacement is an important process that occurs in a shale matrix after hydraulic fracturing and in water-based enhanced oil recovery. Current understanding of this displacement process is limited because of the complicated pore structure and surface properties in shale. In this work, this process and its controlling factors are investigated through a comparative study of three shale samples that have different types of pore systems and wettability. An integrated method of imbibition and multiscale imaging was applied, and a modified oleic tracer that can better represent oil flow was used in imbibition testing and micro-computed tomography (CT) imaging. Scanning electron microscope (SEM) pore characterization was then performed under high magnification with guidance from the micro-CT images showing the changes caused by oil or water imbibition. New insights were obtained on the importance of both wettability and pore size effect on oil recovery and the distribution of residual oil after water-oil displacement. Connectivity of pores with different wettability is also discussed based on 3D analysis and SEM pore characterization. Collectively, these new findings improve the understanding of the complicated process of water-oil displacement and the role of influencing factors. Important implications for improved oil recovery strategy in shale are discussed for different types of reservoir rocks. The integrated imaging and imbibition technique provides a new path for further investigation of improved oil recovery in shale.
Abstract Upper Bakken Shale (UBS) in the Williston Basin is a world class source rock with an average TOC of 11.5 wt.%. and also, a resource play with a history of oil production in the 1990s. Previous studies have suggested that the main reason behind the organic enrichment in UBS is the enhanced preservation potential of organic matter (OM) due to the prevailing reducing conditions in the Williston Basin during the deposition of the UBS. However, redox condition during the deposition of UBS is highly debated with recent interpretations widely ranging from sub-oxic to euxinic-photic zone euxinia. These inconsistencies with regards to the redox condition of UBS arises because interpretations are either based on sedimentary evidences or geochemical proxies. In this paper, we address these contradictions and determine the lateral and temporal variation of the redox condition and sedimentary processes during the deposition of the UBS based on the integration of sedimentary and geochemical evidences from 16 wells spread across the basin. Firstly, we establish the laterally correlatable chemostratigraphic units for UBS based on the integration of lithofacies and associated sedimentary processes determined from core descriptions and thin-section petrography with elemental concentration data acquired by a handheld X-Ray Fluorescence (XRF) analyzer. Then we draw a robust conclusion about the paleoredox conditions of the different chemostratigraphic units of UBS by combining the sedimentary evidences with multiple independent geochemical proxies including i) the absolute concentration of trace elements Mo; ii) covariation pattern of enrichment factor of Mo and U; and iii) the degree of pyritization calculated from Fe-S relationship. Our study identified three correlatable chemostratigraphic units of UBS namely units 1a, 1b and 2 from bottom to top and the redox condition varied temporally and regionally during the deposition of these units. Unit 1a and 1b was deposited predominantly in euxinic conditions with frequent photic-zone euxinia. Whereas, during the deposition of Unit-2, redox-conditions varied laterally across the basin from suboxic to euxinic. This study highlights the significance of integration of different sources of data to develop a robust depositional model for organic-rich shales.
Abstract The Lewis Shale is a turbidite system encompassing sandstones, siltstones, and organic-rich shales, deposited during the last Cretaceous seaway transgression. It is informally subdivided into three members; a lower member (characterized by high clay and organic matter content), a middle member (a mixture of siltstones, shales, and sandstones), and an upper member or Dad sandstone member (with decreasing amounts of sandstone and greenish-grey shales) that can reach up to 2600 ft. in thickness (Almon, 2002). Its lithological characteristics vary depending upon its location in the Lewis depositional basin (eastern Greater Green River Basin). The present study is located in the Sweetwater and Carbon counties in Wyoming. Data includes three cores in the Great Divide Basin and one in the Wamsutter Arch provided by MorningStar Partners/Southland Royalty. Cores contain various lithologies, including shales, siltstones, and sandstones, representing the Lewis Shale's lithologic heterogeneity and complexity. Reservoir quality and lithology are intrinsically related. Therefore, high-resolution reservoir characterization must be performed to understand these different intervals and forecast some of the reservoir properties and possible challenges. Measured and sampled core data includes X-ray Fluorescence (XRF), X-ray diffraction (XRD), and Routine core analyses (RCA). Well-log data obtained from the Wyoming Conservation Commission (WOGCC) and donated by TGS were used to perform correlations, build maps of the different cored intervals, and evaluate its internal characteristics and reservoir quality. Core description and X-ray Fluorescence spectroscopy (XRF) analyses were performed every 0.5 ft. Samples for thin sections and X-ray diffraction (XRD) were taken in areas of interest based on lithology changes. Well-logs were correlated using the Gamma Ray (GR) signature for the cored and adjacent intervals. The objective of this work is to develop a high-resolution reservoir characterization. This analysis is crucial for understanding this play and decreasing uncertainty when planning new well placements. Although there have been several studies that identify the primary minerals and analyze the reservoir quality of some intervals of the Lewis Shale, none has been a high-resolution study combining XRF data, nor have any been oriented to horizontal drilling and unconventional reservoirs (Thyne et al., 2003; Pasternack, 2005, Sapardina, 2012). Correlations helped identify the heterogeneity and possible complications these turbiditic reservoirs can present, such as target pinch out and an increase in clay content that could cause swelling or instability in the wellbore and a possible loss of the well or the need to drill a sidetrack. Furthermore, this was also evidenced in the thin section, XRD, and XRF analyses showing mineralogical variations down to the inches scale, which is lower than the well-log resolution, making it challenging to identify. The overall composition of all the intervals is very consistent with high quartz content, followed by clay and carbonate contents. The presence of illite/smectite swelling clays can increase the wellbore problems and reduce porosity and permeability. According to Wang and Gale (2009), the brittleness of rock or fracability is controlled by several factors such as strength, lithology, texture, effective stress, temperature, fluid type diagenesis, and Total Organic Carbon (TOC). The brittleness index helps quantify some of these factors based on the mineral composition and diagenesis of the rock, without calculating Young's and Poisson moduli. According to Jarvie (2005), minerals that affect this index the most are quartz (the higher the quartz content, the higher the brittleness) and Carbonate, Clay, and TOC content (these decrease the brittleness index). Wang and Gale (2009) also included dolomite as a brittle mineral. However, the brittleness index was not calculated on these cores due to the absence of TOC measurements in some of them and the formula could not be applied. An approximation of how brittle a rock can be based on the formula's principle, where the higher the percentage of quartz and dolomite, the higher the brittleness index. In instances where calcite percentage is high, it can act as a brittle mineral. Dolomite is found as grains and cement, augmenting the rock's brittleness, but it can also decrease its porosity and permeability. Although, in general, the high quartz, calcite, dolomite, and plagioclase content in all the cored intervals makes them particularly brittle, thus facilitating hydraulic fracturing.