Summary We introduce a quick and cost-effective method of estimating horizontal in-situ stress profiles and rock elastic moduli vs. depth from geophysical logs taken in vertical well sections. A multiobjective optimization approach finds the optimum solution for the inversion of in-situ stresses and the rock mechanical parameters from elastic borehole deformations measured by the commonly available four-arm caliper tools. The four-arm caliper log responses also permit quality control (QC) of input and identification and classification of borehole sections that display breakouts and sloughing. The method is applied in the estimation of horizontal in-situ stress profiles and rock deformation moduli vs. depth in Karamay Basin, Northwestern China. The results have demonstrated good agreement with available field in-situ stress measurements, indicating promising broader applications of the method.

Summary The objectives of this study are to perform a fundamental analysis of the mutual interactions between crude oil components, water, hydrocarbon solvents, and clays, and to determine the optimum hydrocarbon solvent in solvent steamflooding for a particular reservoir type. The water/oil emulsion formation mechanism in the obtained oil for steam and solvent steamflooding processes has been studied via intermolecular associations between asphaltenes, water, and migrated clay particles. A series of 21 steam and solvent-steamflooding experiments has been conducted, first without any clays in the oil/sand packing, and then using two different clay types in the reservoir rock: Clay 1, which is kaolinite, and Clay 2, which is a mixture of kaolinite and illite. Paraffinic (propane, n -butane, n -pentane, n -hexane, n -heptane) and aromatic (toluene) solvents are coinjected with steam. Cumulative oil recovery is found to decrease in the following order: no clay, Clay 1, Clay 2. Based on the obtained produced oil analyses, Clay 1 and Clay 2 are found to have an affinity with the water and oil phases, respectively. Moreover, the biwettable nature of Clay 2 makes it dispersed in the oil phase toward the oil/water interface, stabilizing the water/oil emulsions. Paraffinic solvent n -hexane is found to be an optimum coinjector for solvent steamflooding in bitumen recovery.

Summary Surfactant-polymer (SP) flooding has been regarded as an efficient technique for enhanced oil recovery in the development of mature oil fields, especially for those with heterogeneous conglomerate reservoirs. However, people are still unclear about the optimal SP flooding initiation timing (OSPT) that is expected to contribute to the maximum ultimate recovery factor in the case with a limited amount of SP solution injection. Accordingly, this study aims to investigate OSPT through conducting a series of experiments, including nuclear magnetic resonance (NMR) online monitoring, full-diameter coreflooding, and microfluidic study. The fractional-flow curve is used to identify OSPT, of which the effect on the oil recovery is analyzed. OSPT is demonstrated to be dependent on the amount of injected SP solution. An earlier-started SP flooding is favorable for achieving higher oil recovery factors under the premise of sufficiently high SP solution injection [more than 1.5 pore volume (PV)]. With the commonly used 0.65 PV of SP solution in the reservoir scale, OSPT is suggested to be at the moment when a water cut of 80 to 90% is reached. The formation of dense emulsions in the early-started SP flooding affects the performance of the post-waterflooding, which eventually decreases the ultimate oil recoveries because of inadequacy of SP solution. An earlier-started SP flooding contributes to a larger swept volume, but the initial efficiency of the SP flooding is lower than that of the waterflooding when the injection pressure is constant. OSPT is proposed through analyzing the fractional-flow curve in the case of 0.65 PV of SP injection, and the determined OSPT is validated by coreflooding experiments and field data. Moreover, OSPT for the conglomerate reservoir is suggested to be earlier than that for the relatively homogenous sandstone reservoir.

Summary Spontaneous imbibition (SI) is regarded as an effective method to improve the oil recovery in a tight sandstone reservoir, which leads to a significant change in fracturing design and flowback treatment. However, a longtime shut-in period would aggravate the retention of fracturing fluid, which is in contradiction with high production in the field. It is imperative to understand how SI works during shut-in time, so as to maximize the effect of imbibition in oil recovery enhancement. In this study, a series of experiments were conducted to simulate the status of residual oil saturation so that the inner mechanism of imbibition on oil recovery can be investigated. Low-field nuclear magnetic resonance (LF-NMR) was used to provide direct observation of phase changes in different pore sizes. The experimental results show a positive effect of imbibition on residual oil reduction. This phenomenon further elucidates the observations made during the well shut-in, soaking period, and low flowback efficiency. This study aims to understand the mechanism of SI behavior and help to improve the accuracy of production prediction.

Summary Temperature-dependent irreducible water saturation has great implications for heavy-oil production. Especially in processes using thermal methods, the irreducible water saturation varies significantly when temperature rises from the initial reservoir condition to the temperature of injected hot fluids. In this work, the irreducible water saturation retained in a heavy-oil/oil-sands reservoir has been theoretically analyzed as a function of temperature in the view of thermodynamics. This analysis involves oil/water interactions, thermodynamic stability, pendular rings between particles, and a dense random-packing theory. The temperature-dependent irreducible water saturation in two heavy-oil reservoir samples (Coalinga and Huntington Beach) and two oil-sands reservoir samples (Cat Canyon and Peace River) have been analyzed using an oil/water/silica system. The computed results have been compared with published experimental data. The good agreements of the comparison demonstrate the feasibility of the proposed analysis to describe the irreducible water saturation in a heavy-oil/oil-sands reservoir up to 300°C. Through these analyses, the theoretical understandings of temperature-dependent irreducible water in a heavy-oil/oil-sands reservoir have been provided. As temperature increases, the mutual water/oil solubilities are increased by enhanced molecular interactions, as well as the surface energy at an oil/water connecting interface. As a result, the oil/water interfacial tension (IFT) decreases, which diminishes the contact angle and enlarges a water-filled pendular ring between particles at elevated temperatures. Thus, the irreducible water saturation is increased by the enlarged pendular rings in a dense packing porous medium. In addition, this study demonstrates the possibilities to alter the irreducible water saturation appropriately in a heavy-oil/oil-sands reservoir to enhance oil recovery, decrease water cut, save costs of surface oil/water separation, and reduce heat consumption.

Summary A physics-based data-driven model is proposed for forecasting of subsurface energy production. The model fully relies on production data and does not require any in-depth knowledge of reservoir geology or governing physics. In the proposed approach, we use the Delft Advanced Reservoir Terra Simulator (DARTS) as a workhorse for data-driven simulation. DARTS uses an operator-based linearization technique that exploits an abstract interpretation of physics benefiting computational performance. The physics-based data-driven model is trained to fit data increasing the fidelity of the model forecast and reflecting significant changes in reservoir dynamics or physics over its history. The model is examined and validated for both synthetic and real field production data. We demonstrate that the developed approach is capable of providing accurate and reliable production forecast on a daily basis, even if the exact geological information is not available.

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 The modern focused ion beam-scanning electron microscopy (FIB-SEM) allows imaging of nanoporous tight reservoir-rock samples in 3D at a resolution up to 3 nm/voxel. Correct porosity determination from FIB-SEM images requires fast and robust segmentation. However, the quality and efficient segmentation of FIB-SEM images is still a complicated and challenging task. Typically, a trained operator spends days or weeks in subjective and semimanual labeling of a single FIB-SEM data set. The presence of FIB-SEM artifacts, such as porebacks, requires developing a new methodology for efficient image segmentation. We have developed a method for simplification of multimodal segmentation of FIB-SEM data sets using machine-learning (ML)-based techniques. We study a collection of rock samples formed according to the petrophysical interpretation of well logs from a complex tight gas reservoir rock of the Berezov Formation (West Siberia, Russia). The core samples were passed through a multiscale imaging workflow for pore-space-structure upscaling from nanometer to log scale. FIB-SEM imaging resolved the finest scale using a dual-beam analytical system. Image segmentation used an architecture derived from a convolutional neural network (CNN) in the DeepUNet (Ronneberger et al. 2015) configuration. We implemented the solution in the Pytorch® (Facebook, Inc., Menlo Park, California, USA) framework in a Linux environment. Computation exploited a high-performance computing system. The acquired data included three 3D FIB-SEM data sets with a physical size of approximately 20 × 15 × 25 µm with a voxel size of 5 nm. A professional geologist manually segmented (labeled) a fraction of slices. We split the labeled slices into training, validation, and test data. We then augmented the training data to increase its size. The developed CNN delivered promising results. The model performed automatic segmentation with the following average quality indicators according to test data: accuracy of 86.66%, precision of 54.93%, recall of 83.76%, and F 1 score of 55.10%. We achieved a significant boost in segmentation speed of 14.5 megapixel (MP)/min. Compared with 0.18 to 1.45 MP/min for manual labeling, this yielded an efficiency increase of at least 10 times. The presented research work improves the quality of quantitative petrophysical characterization of complex reservoir rocks using digital rock imaging. The development allows the multiphase segmentation of 3D FIB-SEM data complicated with artifacts. It delivers correct and precise pore-space segmentation, resulting in little turn-around-time saving and increased porosity-data quality. Although image segmentation using CNNs is mainstream in the modern ML world, it is an emerging novel approach for reservoir-characterization tasks.

Summary Decline curve analysis (DCA) has been widely applied in production forecasting of wells in unconventional hydrocarbon reservoirs. However, traditional curve-fit-based methods fall short of forecast accuracy due to three weaknesses: first, they cannot capture the reservoir signals not modeled by the underlying DCA model formulas; second, when predicting the production of a target well, the production history of other wells in the geologic formation (which is valuable information) is not considered; third, the wells’ geographic, geologic, wellbore, well spacing, and completion properties, which are highly relevant to production capability, are not used. More recent approaches have begun replacing traditional DCA with machine-learning methods [e.g., random forest (RF), support vector regression (SVR), etc.] for production forecast. Nevertheless, these methods are still suboptimal in detecting similar production trends in different wells, leading to large forecast error. A new and simple method called dynamic production rescaling (DPR) is developed to improve the accuracy of machine-learning DCA (ML-DCA). By combining DPR with common ML-DCA methods, we observe that the error mean, deviation, and skewness can be significantly reduced by 15 to 35% compared with ML-DCA without DPR. The error reduction is 30 to 60% compared with automatic curve fit of the traditional modified Arps DCA model. DPR has been tested successfully on monthly production data of over 20,000 unconventional horizontal wells in the Permian and Appalachian basins for both long- and short-term forecasts. The significant error reduction is consistent across different basins and formations. DPR is computationally efficient, so a large number of wells can be analyzed automatically and quickly. Moreover, the effectiveness and efficiency of DPR is independent of the underlying machine-learning algorithm, further demonstrating its robustness.

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.

Summary Fracturing is the necessary means of tight oil development, and the most common fracturing fluid is slickwater. However, the Loess Plateau of the Ordos Basin in China is seriously short of water resources. Therefore, the tight oil development in this area by hydraulic fracturing is extremely costly and environmentally unfriendly. In this paper, a new method using supercritical carbon dioxide (CO 2 ) (ScCO 2 ) as the prefracturing energized fluid is applied in hydraulic fracturing. This method can give full play to the dual advantages of ScCO 2 characteristics and mixed-water fracturing technology while saving water resources at the same time. On the other hand, this method can reduce reservoir damage, change rock microstructure, and significantly increase oil production, which is a development method with broad application potential. In this work, the main mechanism, the system-energy enhancement, and flowback efficiency of ScCO 2 as the prefracturing energized fluid were investigated. First, the microscopic mechanism of ScCO 2 was studied, and the effects of ScCO 2 on pores and rock minerals were analyzed by nuclear-magnetic-resonance (NMR) test, X-ray-diffraction (XRD) analysis, and scanning-electron-microscope (SEM) experiments. Second, the high-pressurechamber-reaction experiment was conducted to study the interaction mechanism between ScCO 2 and live oil under formation conditions, and quantitively describe the change of high-pressure physical properties of live oil after ScCO 2 injection. Then, the numerical-simulation method was applied to analyze the distribution and existence state of ScCO 2 , as well as the changes of live-oil density, viscosity, and composition in different stages during the full-cycle fracturing process. Finally, four injection modes of ScCO 2 -injection core-laboratory experiments were designed to compare the performance of ScCO 2 and slickwater in terms of energy enhancement and flowback efficiency, then optimize the optimal CO 2 -injection mode and the optimal injection amount of CO 2 slug. The results show that ScCO 2 can dissolve calcite and clay minerals (illite and chlorite) to generate pores with sizes in the range of 0.1 to 10 µm, which is the main reason for the porosity and permeability increases. Besides, the generated secondary clay minerals and dispersion of previously cemented rock particles will block the pores. ScCO 2 injection increases the saturation pressure, expansion coefficient, volume coefficient, density, and compressibility of crude oil, which are the main mechanisms of energy increase and oil-production enhancement. After analyzing the four different injection-mode tests, the optimal one is to first inject CO 2 and then inject slickwater. The CO 2 slug has the optimal value, which is 0.5 pore volume (PV) in this paper. In this paper, the main mechanisms of using ScCO 2 as the prefracturing energized fluid are illuminated. Experimental studies have proved the pressure increase, production enhancement, and flowback potential of CO 2 prefracturing. The application of this method is of great significance to the protection of water resources and the improvement of the fracturing effect.

Summary Applying the realistic cementation exponent ( m ) in Archie’s equation is critical for reliable fluid-saturation calculation from well logs in shale formations. In this study, the cementation exponent was determined under different confining pressures using a high-salinity brine to suppress the surface conductivity related to the cation-exchange capacity of clay particles. A total of five Ordovician shale samples from the Canning Basin, Australia, were used for this study. The shale samples are all illite-rich with up to 60% clay content. Resistivity and porosity measurements were performed under a series of confining pressures (from 500 to 8,500 psi). Nuclear magnetic resonance (NMR) was used to obtain porosity and pore-size distribution and to detect the presence of residual oil. The complex impedance of samples was determined at 1 kHz to verify the change in pore-size distribution using the POLARIS model (Revil and Florsch 2010). The variation of shale resistivity and the Archie exponent m at different pressures is caused by the closure of microfractures at 500 psi, the narrowing of mesopores/macropores between 500 and 3,500 psi, and the pore-throat reduction beyond 3,500 psi. This study indicates that unlike typical reservoirs, the Archie exponent m for shale is sensitive to depth of burial because of the soft nature of the shale pore system. An equation is developed to predict m under different pressures after microfracture closure. Our study provides recommended experimental procedures for the calculation of the Archie exponent m for shales, leading to improved accuracy for well-log interpretation within shale formations when using Archie-basedequations.

Summary In this paper, we present an experimental study that explores the potential links between the imbibition capillary pressure P ci and the pore systems and/or mineralogy for carbonate reservoirs undergoing waterflood. A systematic workflow has been formulated to ensure the data quality of P ci , minimize uncertainty in deriving P ci from centrifuge tests, and analyze the data considering the pore-size distribution from mercury injection capillary pressure (MICP) and mineralogy from Quantitative Evaluation of Minerals by Scanning Electron Microscopy (QEMSCAN). The workflow starts with assessing the centrifuge production data for gravity-capillary equilibrium at each speed. Then, the quality-checked data are used to generate six different P ci curves using analytical and numerical models. The resulting curves provide a measure of the variability in solutions for various rock types and assist in the selection of the most-representative P ci curve. Finally, the representative P ci curves of all rock samples are analyzed together with the MICP and QEMSCAN data to examine the change in P ci curves as a result of changes in the number and character of rock types, pore systems, dominant pore-throat radii, and mineralogy. Findings from this study shed light on the impact of mineralogy and pore systems on P ci . From the mineralogy perspective, the presence of dolomite, microporous calcite, or rutile and anatase (TiO 2 ) within the rock composition is found to affect the P ci of the carbonate samples used in this study. The rock samples with these minerals should be separated from other bimodal samples before attempting to obtain a correlation between P ci and pore systems. The data analysis further reveals that some bimodal samples of medium permeability yield a better waterflood imbibition efficiency than those of the high-permeability samples. This observation is attributed to a better communication between the micropore and macropore systems, and a closer proximity of the peak radii of the micro- and macropore systems of the medium-permeability samples.

Summary The injection of carbon dioxide (CO 2 ) into saline aquifers is highlighted as an effective technique to permanently secure anthropogenic gas produced from high CO 2 gas fields in the Southeast Asia region. However, previous studies indicate that CO 2 injectivity can be impaired primarily due to the interactions between CO 2 /brine/rock. In this paper, we investigate the effect of a CO 2 injection scheme, rock permeability, brine type, and salinity on CO 2 injectivity, which is presented by permeability alteration. A CO 2 coreflood experiment and the characterization of the rock and effluent produced are presented. Furthermore, core samples with different permeabilities of the typical geological storage for sequestration were selected and analyzed using X-ray fluorescence (XRF), X-ray diffraction (XRD), and field-emission scanning electron microscopy equipped with energy dispersive X-ray spectroscopy (FESEM-EDX). The cores were then saturated with synthetic brine composed of 6,000, 30,000 or 100,000 parts per million (ppm) of either sodium chloride (NaCl), potassium chloride (KCl), or calcium chloride (CaCl 2 ). Subsequently, the core samples were injected by either supercritical CO 2 (scCO 2 ), CO 2 -saturated brine, or CO 2 -saturated brine followed by scCO 2 . The fines particles from the collected effluent were separated for further analysis. The results indicate that a CO 2 injection scheme, injection flow rate, brine salinity, and initial rock permeability are the principal factors that contribute to the permeability alteration of the core samples. It was also found from FESEM-EDX analysis of the produced fines that the precipitated salt, silica grains, and kaolinite migrated during scCO 2 injection, suggesting the dissolution and precipitation of minerals. This phenomenon led to the migration of particles, some of which plugged the pore spaces and reduced the permeability. Besides, the core saturated with CaCl 2 brine was the only sample with improvement in permeability after the CO 2 flooding experiment.

Summary The design of oil-recovery processes by gas injection or vapor solvent relies on the knowledge of diffusion coefficients to enable meaningful production predictions. However, laboratory measurements of diffusion coefficients are often performed on bulk fluids, without accountability for the hindrance caused by the pore-network structure and tortuosity of porous media. As such, our ability to predict effective diffusion coefficients in porous rocks is inadequate, and additional laboratory work is needed to investigate the impact of the medium itself on transport by diffusion. A vast number of studies focus on measurements of diffusion coefficients on simple binary systems and a few heavy-oil systems. This study proposes an experimental methodology, based on the pressure-decay technique, to measure diffusion of gas (methane) in crude oil within a porous rock. A diffusion experiment of gas into bulk oil (without porous medium) provides an upper-limit estimation of the gas/liquid-diffusion coefficient. Diffusion experiments using Indiana Limestone and Bakken Shale provide insight into different degrees of rock-matrix hindrance. Two analytical models and one numerical model were implemented to estimate the diffusion coefficients from time-dependent experimental pressure-decay data. These diffusion coefficients were found to be in agreement with literature on corresponding data, demonstrating the validity of the modeling approaches used. Results indicate considerable hindrance to diffusion in porous media relative to bulk oil and relate to the tortuosity of the rock matrix. The diffusion coefficient of methane in bulk oil was found to be 3.8 × 10 − 9 m 2 / s . In the limestone sample, this diffusion coefficient dropped by one order of magnitude, ranging between 1.5 and 6.5 × 10 − 10 m 2 / s , and decreased by another order of magnitude in the Bakken Shale sample to 2.0 × 10 − 11 m 2 / s . By comparing the influence of tortuosity with increasing the initial pressure, results show that tortuosity has a more-significant impact on the effective diffusion coefficient than the initial pressure.

Summary Designing and selecting the proper sand control mechanism for horizontal wells in unconsolidated heavy-oil reservoirs tend to be underlooked in some cases. Standalone completions pose some sand control challenges, which could jeopardize the oil production or even lead to critical problems. Massive sand production, screen/formation plugging, hot spots, and mechanical integrity failures are some of the well-known issues. This study attempts to optimize the slotted liner design for horizontal wells in a heavy-oil field in Colombia. A careful selection of representative core data was made to study the variation of sand particle-size distribution (PSD) within the development area. Reservoir fluid properties were analyzed. Based on PSD variation and current design criteria in the industry, several seamed slotted-liner configurations were proposed as an alternative completion for testing. Later, a series of large-scale sand retention tests (SRTs) were performed to assess the selected alternatives under typical field production conditions. The effects of aperture size and open-to-flow area were investigated to evaluate flow and sand control performance. This investigation started with a detailed study of the PSD, particle shape variation, and composition of fines in the development area. The PSD then classified into four distinct minor and major sand facies, ranging from medium to very coarse sand with different fines content. Further investigations have shown that current design is only suitable for a limited number of the PSDs, while the overall PSD classes indicate the requirement for wider slot aperture sizes. The results of the SRTs indicated that the flow performance of the screen is mainly controlled by the slot aperture. Choosing the optimized aperture size avoids unacceptable sanding even for the multiphase flow scenarios with gas. Results also indicated that by increasing the aperture size and application of the seamed slots for the studied formation, plugging could be mitigated. A comprehensive sand control design workflow for cold primary heavy-oil production in horizontal wells is presented in this work. The current study is one of the first that investigates and compares conventional straight slotted liners with seamed slotted liners at a larger scale for this field. Moreover, this study helps to better understand the effect of design parameters of seamed slotted liners on sand control, flow performance, and plugging tendency.

Summary The mobility of salt rocks may cause problems, such as stuck pipe, high torque, casing collapse, and hole closure, promoting enormous losses in different areas. The drilling mud weight generates a hydrostatic pressure that serves as a counterpressure to the displacement of the salt. Sometimes this measure is not enough, leading to the backreaming operation, which reconditions the diameter of the wellbore to its original state. Given the importance of backreaming during drilling operations in salt rocks, its incorporation into computational tools is necessary. Through the finite element method (FEM), we developed a program to identify and simulate the effects of the backreaming operations in vertical wells in the presence of salt layers. We proposed a simulator that associates 1D axisymmetric multilayers with unit thickness through a coupling strategy between them, considering a lesser number of degrees of freedom when compared to conventional 2D modeling. We checked the performance of multilayers strategy when compared with 2D axisymmetric modeling of the hole closure problem in the commercial software ABAQUS® (Dassault Systèmes, Vélizy-Villacoublay, France); for the radial displacement histories, the multilayer strategy presented similarity with ABAQUS for cases that consider interaction, with the advantage of a low computational cost provided by the 1D formulation. We demonstrated the modeling of backreaming through the proposed tool.

Summary Cement-rock interface is a major component of the wellbore barrier system. Leakage may result from the poor bonding between cement and rock interface. In this paper we investigate possible factors that may affect the cement-rock interface bonding. More specifically, integrity of the cement-rock interface was characterized using micro-computed tomography (CT) and environmental scanning electron microscopy (ESEM). Hollow cylinder rock samples were prepared by using rock samples (e.g., Banff dolostone, Pekisko limestone, Doig sandstone, Notikewin siltstone, Montney siltstone, and Wilrich siltstone) collected from different Alberta wells at various depths. Two abandonment cement blends were injected into the rock open hole. After curing the cement-rock samples in water at ambient temperature (≈21°C) and 1,500 psi for 7 days, the samples were then processed into thin sections. By using ESEM (0.05-µm resolution) and micro-CT (11.92-µm resolution) techniques, the 2D and 3D models of the cement-rock interface were developed. Energy-dispersiveX-ray spectroscopy (EDS) was conducted to analyze chemical characteristic of the cement-rock samples. Using the CT images, computational fluid dynamics (CFD) models were built to simulate fluid flow through the cement-rocksamples. For both cement and rock, there is a nonuniform porosity distribution in radial and axial directions. For most of the cement-rock samples, the highest porosity region in the cement column was found at the cement-rock interface. Optimizing the chemistry of the cement system enhances the cement-rock interface bond by effectively reducing the gap between cement and rock observed in ESEM images. Although cement migration was observed in the rough rock surface in porous rocks, the rock interface and matrix zones have almost identical element concentrations. For the investigated samples, the chance for significant chemical reaction at the cement-rock interface is minimal. CFD simulation based on digital cement models showed that the cement-rock interface has more chance to act as the main flow pathway when intact (low permeability) caprock exists. The sample preparation, image analysis and simulation methods used in this study can be also applied to other cement interface studies (e.g., cement-casing, casing-cement-rock). From the practical field application point of view, the results presented here would help to have a better understanding of the requirements for designing optimum cement formulations to establish effective zonal isolation and reduce the greenhouse gas emissions from oil and gas wells.

Summary Severe formation damage often occurs during the drilling process, which significantly impedes the timely discovery, accurate evaluation, and efficient development of deep tight clastic gas reservoirs. The addition of formation protection additives into drilling fluid after diagnosing the damage mechanism is the most popular technique for formation damage control (FDC). However, the implementation of traditional FDC measures does not consider the multiscale damage characteristics of the reservoir. The present study aims at filling this gap by providing a complete and systematic damage control methodology based on multiscale FDC theory. First, the characteristics of multiscale seepage channels were described through petrology, petrophysics, and well-history data. Subsequently, based on laboratory formation damage evaluation experiments, the formation damage mechanism of each seepage scale was determined. Finally, based on the multiscale formation damage mechanism, a systematic multiscale FDC technology was proposed. Through the use of optimized drilling fluid based on multiscale FDC theory, high-permeability recovery ratio (PRR), high-pressure bearing capacity of plugging zone, and low cumulative filtration loss were observed by laboratory validation experiments. Shorter drilling cycle, less drill-in-fluid loss, lower skin factor, and higher production rates were obtained by using the optimized FDC drilling fluid in field application. This multiscale FDC theory shows excellent results in minimizing formation damage, maintaining original production capacity, and effectively developing gas reservoirs with multiscale pore structure characteristics.

Summary Fractured reservoirs account for more than one-half of the global oil and gas output and thus play a pivotal role in the world’s energy structure. Under diagenesis, rocks become dense, and tectonic fractures easily form under subsequent tectonic movement. These tectonic fractures are the main seepage conduits of tight sandstone reservoirs and are important determinants of whether a tight sandstone reservoir can have high, stable oil and gas production. The influence of multistage tectonic movement has led to well-developed fractures in the Ordos Basin in central China. In the process of reservoir development, the effective stress on the fracture surface increases because of the decrease in pore pressure, and the fracture aperture, porosity, and permeability also change accordingly. Therefore, modeling of the dual porosity and dual permeability of fractured reservoirs requires a dynamic 4D modeling process related to time. In this paper, we propose a 4D modeling method of dual porosity and dual permeability in fractured tight sandstone reservoirs. First, the porosity and permeability distribution of the reservoir matrix are established based on reservoir modeling. Based on geomechanical modeling, the density and occurrence of natural fractures are predicted by the paleostress field. The in-situ stress field is used to analyze the fracture aperture, and the variation in the fracture aperture during the development process is analyzed along with the variation in the in-situ stress in the development process to realize 4D modeling of the porosity and permeability of fractured reservoirs. The total porosity of the fracture is 0 to 8 × 10 −3 %, and the principal value of the planar permeability of the fracture is 0 to 3 × 10 −3 µm 2 ; the principal value of the fracture permeability is concentrated in the direction of 65 to 70° east-northeast. The simulated fracture porosity stress sensitivity index is distributed between 0 and 0.2, and the fracture permeability stress sensitivity index is distributed between 0 and 0.4. The Young’s modulus of the rock, in-situ stress parameters, and sound velocity in the rock are important factors affecting the fracture stress sensitivity.