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Coalbed methane (CBM) seepage is a significant geological factor affecting the capacity of CBM wells. Using the example of the Qinnan-East Block of the Qinshui Basin, in this work, the CBM seepage law under different in situ stresses, coal reservoir pressures, and temperatures is systematically analyzed using on-site well test data. A permeability calculation model that includes the coal reservoir stress, pressure, and temperature is established, and the coal permeability and its control mechanism under the action of multiple fields are revealed. The results demonstrate that the in situ stress, pressure, and temperature in the study area increase linearly with increasing depth. The coal reservoir geothermal gradient is 0.72–2.11 °C/100 m, and the mean value is 1.67 °C/100 m. The coal reservoir geothermal gradient rises with an increasing depth as a logarithmic function. The permeability of the coal reservoir is 0.01–0.20 × 10−3 μm2, the mean value is 0.05 × 10−3 μm2, and the CBM seepage under the action of multiple physical fields is relatively low. With increasing effective stress and temperature, the permeability continuously decreases following a negative exponential function. The CBM seepage is tightly bound to the fracture aperture and is controlled by the change in the in situ stress, the pore fluid pressure, and the temperature stress. [ABSTRACT FROM AUTHOR]

The objective of this study is to construct a refined microscopic transport model that elucidates the transport mechanisms of gas flow within micro-nano pores and fractures. The collective impact of various microscopic transport mechanisms was explained through the apparent permeability model, specifically related to gases such as methane and carbon dioxide, within the shale matrix. The apparent permeability models, taking into account microscopic transport mechanisms such as slippage flow, Knudsen diffusion, transition flow, and surface diffusion, were established individually. Subsequently, the influencing factors on apparent permeability were analyzed. The results demonstrate that the apparent permeability of the shale reservoir matrix is significantly influenced by pore pressure, temperature, pore size, and total organic carbon (TOC). As pressure decreases, the apparent permeability of Knudsen diffusion and surface diffusion increases, while the apparent permeability of slippage flow decreases. In addition, the apparent permeability of the reservoir matrix initially decreases and then increases. With increasing temperature, the apparent permeability of slippage flow, Knudsen diffusion, and surface diffusion all increase, as does the apparent permeability of the reservoir matrix. As pore size increases, the apparent permeability of surface diffusion and Knudsen diffusion decreases, while the apparent permeability of slippage flow and the reservoir matrix increases. Furthermore, an increase in TOC leads to no change in the apparent permeability of slippage flow and Knudsen diffusion, but an increase in the apparent permeability of surface diffusion and the reservoir matrix. The model presented in this paper enhances the multi-scale characterization of gas microflow mechanisms in shale and establishes the macroscopic application of these micro-mechanisms. Moreover, this study provides a theoretical foundation for the implementation of carbon capture, utilization, and storage (CCUS) in shale gas production. [ABSTRACT FROM AUTHOR]

Permeability is a required parameter for studying aquifer properties. However, for sandstone aquifers with low permeability, it is difficult to measure permeability directly through experiments. Based on fractal theory and the J function, a new method to calculate the permeability of a sandstone aquifer is derived. This work first solves the J function under each water saturation according to its definition. Combined with mercury pressure data, the J function and logarithmic curve equation of water saturation are then fitted by the drawing method, and the fractal dimension and tortuosity of the aquifer are further solved. Finally, the aquifer's permeability is calculated using the new permeability calculation method. To verify the accuracy of the proposed method, 15 rock samples from the Chang 7 Group, Ordos Basin, are taken as research objects. The permeability is calculated using the new method combined with mercury injection data and aquifer characteristic parameters, and the results are compared with the real permeability. The relative error of most samples is <20%, which shows the permeability calculated by this method is accurate and reliable. The effects of fractal dimension, tortuosity, and porosity on permeability are also analyzed. [ABSTRACT FROM AUTHOR]

Tight reservoirs have poor physical properties and complex pore structures, and well production is often affected by the starting threshold gradient, stress sensitivity, and water blockage. In this paper, the numerical simulation method is used to make these three factors equal. In addition, normalized influence coefficient analysis and grey relation analysis are used to investigate the degree of influence of each factor on well production. In this study, three methods are developed to set the threshold pressure gradient according to the permeability zoning, and the effect of reservoir heterogeneity is considered to set the threshold pressure gradient for unconventional reservoirs. The equivalent accuracy of the numerical simulation of the threshold pressure gradient can be improved compared to the traditional method. Stress sensitivity and water blockage effects are equated by correcting for rock compressibility coefficient and gas relative permeability. The fit rate of the gas well production history is improved by 2–3% after considering complex factors. The inclusion of the complex factors reduces the reservoir energy mobilization. The threshold pressure gradient results in an additional pressure reduction of about 1.8 MPa around the gas well. Residual gas identification and development is helped by clarifying the effect of complex factors on formation pressure When only the effect of a single factor is considered, water blockage has the most significant effect on gas well production, followed by threshold pressure and the weakest stress sensitivity. When several factors are considered together, the effect of stress sensitivity is increased. [ABSTRACT FROM AUTHOR]

Recently, many researchers have focused on reservoir production optimization because it is one of the most essential processes in closed-loop reservoir management. Surrogate-assisted production optimization in particular has received a lot of research attention. This technique applies a simple yet vigorous approximation model to substitute expensive numerical simulation runs. However, almost all the existing methods independently use a single approximation model and neglect the potential synergies between these models. In order to make full use of the potential synergies of these existing approximation models, a novel multi-fidelity (MF) surrogate-assisted multi-objective production optimization (MOPO) method based on transfer stacking (MFTS-MOPO) is proposed. In the MFTS-MOPO method, the radial basis function network and support vector regression surrogate models are applied to approximate the high-fidelity (HF) model as the two additional low-fidelity (LF) models. Then a multi-fidelity surrogate model is adopted to evaluate objectives during the optimization process by transferring the two additional and streamline low-fidelity models to the computationally expensive high-fidelity model. Furthermore, two sampling infill strategies are applied to efficiently improve the quality of the multi-fidelity surrogate model. The uniqueness of the proposed MFTS-MOPO method is that the transfer stacking technique is employed to efficiently use the information from different fidelity models to establish the MF surrogate model and the infill sampling strategy used to improve its performance. In addition, three benchmark problems and two reservoirs with different scales were applied to illustrate the effectiveness and accuracy of the MFTS-MOPO method. It was found that the MFTS-MOPO method had superior performance in convergence and diversity than other conventional methods. [ABSTRACT FROM AUTHOR]

In recent years, the surrogate-assisted method, which is one of the most promising ways for reducing the computational burden of numerical simulation–based water-flooding reservoir production optimization, has been widely applied by researchers worldwide. Meanwhile, there are different fidelity models that can be applied to extract samples for establishing a surrogate model. However, most of the researches neglected the potential synergies between low-fidelity (LF) and high-fidelity (HF) samples. In this study, therefore, a rapid intelligent multi-fidelity support vector regression (SVR) model–assisted multi-objective production optimization method, namely, MFSVR-MOPO, is proposed to lessen the computational burden of the numerical simulation–based production optimization. The uniqueness of this proposed method is that the LF and HF samples are mapped to a high-dimension space by the kernel function of the SVR, and the relationships between variables and objectives are evaluated by a linear model. Moreover, the gray wolf algorithm was applied to search for the optimal hyperparameters of the SVR model so as to improve the evaluation accuracy. Two frequently used production optimization synthetic reservoirs with different scales were studied to illustrate the effectiveness and accuracy of the MFSVR-MOPO method. The results showed that the MFSVR-MOPO method performed comparably with the HF model–based method in terms of convergence and diversity, but reduced the number of simulation runs on the two reservoirs by approximately 108 times and 50 times, respectively. [ABSTRACT FROM AUTHOR]

The resource potential of tight sandstone reservoirs in China is huge, and these reservoirs have typical characteristics such as complex lithology, low sandstone maturity, strong diagenesis, small pore throat, low natural capacity of producing wells, and strong nonhomogeneity. During development, some production wells suffer from low production and rapidly decreasing production of tight sandstone geological sweet spots. Based on the above understanding, unlike geological sweet spots considering the main parameters such as porosity, permeability, and oil saturation, four engineering sweet spot parameters were integrated and optimized in this study, namely, brittleness index, stress difference coefficient, fracture toughness, and natural weak surface. According to the characteristics of each parameter, a method is proposed to combine the probability index of a complex fracture system with the probability index to obtain a higher reservoir stimulation volume, and a method was established to evaluate engineering sweet spots of tight sandstone reservoirs. Using this evaluation method, an evaluation was conducted in this study for engineering sweet spots reservoir stimulation by combining geological and logging interpretation with a tight reservoir production well in Block C of Ordos Basin as the study target; the correlation between engineering sweet spots index FI and daily oil production was 0.67. On this basis, 5 production wells were selected in the area, and a comparative verification of the engineering sweet spots was conducted in this study using the criteria of the evaluation method. The evaluation test oil results of the evaluation method are considered to be more reliable and realistic, and have a certain guiding role on the field development of production wells in tight sandstone reservoirs. [ABSTRACT FROM AUTHOR]

Multi-objective well control optimization, which considers simultaneous optimization of more than one objective, has become an essential tool for efficient intelligent decision-making about well control parameters. In general, multi-objective well control parameter optimization involves numerical simulation, which is computationally expensive. Surrogate-assisted methods that use a simple yet rigorous approximation model have shown great potential in reducing the need for expensive numerical simulations. In order to strike a balance between reducing computational burden and enhancing accuracy of a surrogate model, we introduce here a semi-supervised learning method called tri-training surrogate-assisted multi-objective optimization (MOO–TTSA), which is based on radial basis function network (RBFN) and non-dominated sorting genetic algorithm-II (NSGA-II) to assist the optimization process. The uniqueness of this method is that a tri-training strategy is applied to enrich the training data set by selecting solutions with high-confidence fitness to renew the surrogate model at each generation so as to obtain better accuracy and lessen the computational burden. In this way, the number of simulation runs is reduced while the accuracy of the surrogate is guaranteed. To the best of our knowledge, this is the first time that a combination of tri-training technique and MOO is used for reservoir well control problems. The MOO–TTSA method was applied to two benchmark problems and two synthetic reservoirs. The results showed that the MOO–TTSA method reduced the number of simulation runs on the two reservoirs, one for about 160 times and the other for 50 times. Besides, the hypervolumes of both the benchmark and reservoir problems of MOO–TTSA were similar with those of the simulation-based NSGA-II method (NSGA-II), but superior to those of the single static surrogate model-based NSGA-II method (RBFN–NSGA-II). It was shown that the MOO–TTSA method was more efficient, superior and converged faster compared to the other conventional optimization models. [ABSTRACT FROM AUTHOR]

One of the main techniques for the exploitation of shale oil and gas is hydraulic fracturing, and the fracturing fluid (slick water) may interact with minerals during the fracturing process, which has a significant effect on the shale pore structure. In this study, the pore structure and fluid distribution of shale samples were analyzed by utilizing low-pressure liquid nitrogen adsorption (LP-N2GA) and nuclear magnetic resonance (NMR). The fractal analysis showed that the pore structure of the sample was strongly heterogeneous. It was also found that the effect of slick water on pore structure can be attributed to two phenomena: the swelling of clay minerals and the dissolution of carbonate minerals. The swelling and dissolution of minerals can exist at the same time, and the strength of them at different soaking times is different, leading to the changes in specific surface area and pore size. After the samples were soaked in the slick water for two days, the contact angle reached the minimum value (below 8°), which means the sample is strongly hydrophilic; then the contact angle increased to above 38° with longer soaking times. The connected pore space in the shale matrix is enlarged by the soaking processing. Therefore, an in-depth understanding of the interaction between the fracking fluid and shale is essential to deepen our understanding of changes in the pore structure in the reservoir and the long-term productivity of shale gas. [ABSTRACT FROM AUTHOR]

Low-permeability oil reservoirs account for more than two-thirds of China's proven reserves, and most of them are multilayered; the traditional sweet spots focus on single-layered reservoirs. The sweet spots of low-permeability reservoirs have two meanings: the geologically superior reservoir and the beneficial development of the reservoir. In this study, a concept of reservoir stratification coefficient is proposed to evaluate the characteristics of multilayered reservoirs, and three indicators are proposed, namely, reservoir stratification coefficient, energy storage coefficient, and stratigraphic coefficient, as the indicators of sweet spots of multilayered reservoirs. The three indicators are combined into a single indicator using a weighted approach, and the sweet spots can be identified based on the combined indicator. The Xiliu A area of the North China oilfield was selected for a case study. According to the structural, sedimentary, and reservoir characteristics of the block, combined with the development and production conditions, the Sha 3 Member I oil group was selected as the study object of sweet spots of the low-permeability reservoir. The results show that the reservoir stratification coefficient, energy storage coefficient, and stratigraphic coefficient proposed in this study are effective indicators for the preferential selection of sweet spots, which can reflect the longitudinal heterogeneity, energy storage size, and flow capacity of multilayered reservoirs. After a comparative analysis with actual blocks, it was found that the results obtained using the method are consistent with the actual capacity of the reservoir. The production capacity is high. The evaluation effect is ideal, and the applicability is good. Thus, this study provides a new technical method for the evaluation of similar multilayered reservoirs. The findings of this study can help for a better understanding of the development and production conditions and optimization basis of low-permeability reservoirs. [ABSTRACT FROM AUTHOR]

Tight oil resources have become the focus of unconventional oil and gas exploration and development. Well placement is an essential factor determining the development of a field. Oil wells should be located in the area with favorable criteria for development. These areas should be screened based upon oil and gas enrichment of the reservoir. The influencing factors and analysis theory of an enrichment area are summarized in this paper. Two types of methods evaluating areas favorable for tight oil and gas production are explained here as well, including model prediction and the combination of geological modeling and reservoir simulation. The area with favorable geological, engineering, and economic attributes has the best development potential. The productivity potential can be used as one basis for selecting areas favorable for production. Based on the previous concept of productivity potential, combined with the characteristics of a tight oil reservoir, this study modified the evaluation of productivity potential, and the calculated potential area was the priority for well placement. The modified equation of productivity potential comprehensively considers effective pore pressure, mobile oil saturation, porosity, permeability, effective thickness, distance from the boundary, and threshold pressure gradient. A tight reservoir was taken as an example for calculation, and the results of the modified method, original productivity potential method, and reserve abundance calculation method are discussed. Two new wells were arranged in the favorable areas obtained by different productivity potential evaluation methods, and the production was calculated under the same parameters for each method. The recovery of this area was 51.65%, which is 1.73% and 2.84% higher than that of the other two methods. [ABSTRACT FROM AUTHOR]

The development of coalbed methane not only ensures the supply of natural gas but also reduces the risks of coal mine accidents. The micropore structure of coalbed methane reservoir affects the seepage of coalbed methane; improvement of pore structure is one of the effective methods to enhance the efficiency of coalbed methane exploitation. In this study, low-pressure nitrogen gas adsorption, specific surface area analysis, nuclear magnetic resonance spectroscopy, and centrifugation experiment were used to evaluate the effect of ethanol on coal microscopic pore structure and fluid distribution during hydraulic fracturing. Seven coal samples were collected from the No. 3 coal seam in Zhaozhuang Mine, Qinshui Basin. The samples are mainly composed of micropores, transition pores, and mesopores. The experimental results show that ethanol can significantly change the pore structure by increasing the pore diameter. The average specific surface area, pore volume, and pore diameter of rock samples before ethanol immersion are 1.1270 m2/g, 0.0104 cm3/g, and 14.20 nm, respectively. The three parameters of rock samples after ethanol immersion are 0.5865 m2/g, 0.0025 cm3/g, and 29.37 nm. Ethanol improves the connectivity between micropores and mesopores. The average irreducible fluid saturation of samples saturated with formation water after centrifugation is 86%, and the average irreducible fluid saturation of samples soaked in three concentrations of ethanol solution decreases. It is considered that an ethanol solution of 0.4% concentration has the best effect on improving the pore structure and fluid distribution. [ABSTRACT FROM AUTHOR]

The optimization of oil field development scheme considering the uncertainty of reservoir model is a challenging and difficult problem in reservoir engineering design. The most common method used in this regard is to generate multiple models based on statistical analysis of uncertain reservoir parameters and requires a large number of simulations to efficiently handle all uncertainties, thus requiring a huge amount of computational power. In order to reduce the computational burden, a method which combines reservoir simulation, an economic model, polynomial chaos expansion with response surface methodology, and Levy flight particle swarm optimization (LFPSO) algorithm is proposed to determine the optimal injection-production parameters with reservoir uncertainties at a reasonable computational cost. This approach is applied to a five-spot well pattern optimization design for obtaining the optimal parameters, including oil-water well distance, injection rate, and bottom hole pressure, while considering the uncertainties of porosity, permeability, and relative permeability. The results of the case study indicated that the integrated approach is practical and efficient for performing reservoir optimization with uncertain reservoir parameters. [ABSTRACT FROM AUTHOR]

Studies on stress sensitivity of relative permeability in the laboratory were mostly carried out by varying overburden pressure at constant pore pressure (PP). However, in a real oilfield situation, changes in net stress are induced by changes in PP rather than overburden pressure. This research presents the effect of PP variation at a confining stress of 25 MPa on water–oil and silica nanofluid–oil relative permeability curves. Results showed that, at low PP variations of 0.1, 2, and 5 MPa, two-phase flow parameters exhibited distinct trends. Thus, for water–oil relative permeability, initial water (Swi) and residual oil (Sor) saturations both decreased as PP increased. End-point oil Kro (Swi) and water Krw (Sor) relative permeabilities both increased for water flooding. Similar trends were observed for nanofluid flooding. End-point mobility ratio and displacement efficiency both increased with increase in PP within this range for water and nanofluid flooding. At 10 MPa PP, Swi decreased compared to low PP variations, while Sor increased significantly. Similar observation was made for nanofluid flooding except for Sor which had moderate increment. End-point mobility ratio increased significantly for water flooding, but had a slight increase for nanofluid flooding compared to low PP variations. Displacement efficiency decreased for both water and nanofluid flooding compared to low PP variations. At the same PP, water–oil and nanofluid–oil relative permeabilities showed similar Swi and Kro (Swi) but differing Sor and Krw (Sor). The findings provide insights into the effect PP variation on relative permeability and would be important in flooding design considerations. [ABSTRACT FROM AUTHOR]

Silica nanofluids have proven to be successful in improving hydrocarbon recovery in the petroleum industry, and increased demand for hydrocarbons has necessitated its application in low-permeability reservoirs. In recent times, surface coating of nanoparticles has been employed to reduce its retention in porous media, but this does not entirely eliminate nanoparticle attachment to pore walls. Knowledge of changes that occur in pore wall and structure such as specific surface area (SSA), pore size distribution and total pore volume (TPV) would be useful in understanding retention mechanisms. This study used nitrogen adsorption technique in studying changes in pore structure due to silica nanofluid treatment. The Brunauer–Emmett–Teller theory and Barrett–Joyner–Halenda adsorption model were used in determining SSAs and TPVs, respectively. SSA, adsorbability and TPV increased in treated samples compared to untreated samples and the rates of change increased with treatment time due to extra pores induced by nanoparticle coagulation. Percent changes in TPV matched closely with SSA and was responsible for increments in the latter. Scanning electron micrographs confirmed coagulation of nanoparticles which increased with treatment time and introduced pseudo-pores on pore walls, resulting in increase in TPV. Increase in differential pore volume was observed for the entire studied range of 2–100 nm except for 3–4 nm which showed no changes in all samples. Severity of differential pore volume increased with treatment time. This study provides insights into nanoscopic changes that occur on pore walls and structure when employing silica nanoparticles in improving hydrocarbon recovery in low-permeability hydrocarbon reservoirs. [ABSTRACT FROM AUTHOR]

The proposed dynamic prediction model is based on the occurrence and migration law of coalbed methane and on the pseudo-steady state diffusion model. The model integrated multi-phase flow theory and material balance equation. It is established by considering not only desorption and diffusion but also crossflow. Moreover, the calculation results show the rationality of the method used. The research analyzes the effects of crossflow factor and diffusion coefficient on development effectiveness. The effect of crossflow factor is obvious in the late production stage but not in the early stage. The diffusion coefficient affects gas production during the exploitation stage. [ABSTRACT FROM PUBLISHER]

Shunbei Oilfield is characterized by substantial heterogeneity and a complex oil–water relationship. The water-oil interface is dynamically changing, and it is a crucial parameter for reserve calculation and evaluation. The main purpose is to analyze the effect of fluid flow in multi-scale media on the water-oil interface. It is well known that the fracture-cavity reservoirs have well-developed fractures and karst caves, and their distribution is complex in Shunbei Oilfield. This paper presents a way to simplify the fracture-cavity system first, then uses a unit of oil wells as a system to study the water-oil interface, which avoids impact on the water-oil interface due to oil production. A detailed step by step procedure for solving the semi-analytical solution of water-oil interface in a fracture-cavity reservoir by using an explicit algorithm and a successive steady-state method is presented. The solution can be used to investigate water-oil interface behavior. In this paper, we validated this method with the actual data for a relatively similar actual reservoir. Sensitivity analyses about the effects of the main parameters including production rates, cave volume and initial oil–water volume ratio on interfacial migration velocity are also presented in detail. The water breaking time of oil wells is fully investigated. The water-oil interface movement chart under different development conditions is established to predict the water-oil interface in the late stage of oil well production and extend the waterless developing period. Being based on this chart, a water breakthrough warning can be realized, and oil recovery can be improved. The findings of the research have led to the conclusion that the rising speed of water-oil interface is proportional to the production rate, on the contrary, it is inversely proportional to cave volume and initial oil–water volume ratio. As well production goes on, the water-oil interface rises at different rates. After the well is put into production for one year, the water-oil interface rises by 16.38%, 12.56% and 4.24% according to the condition that production rate is 10%, the initial oil–water volume ratio is 0.7, and the cave volume is 100 × 104 m3. This method is not only suitable for any period and any well type in the development of Shunbei Oilfield; it also has the function of calculating the real-time water-oil interface of a single well and multi-wells. This new method has the characteristics of easy calculation and high accuracy. The method in this paper can be further developed as it has great applicability in fracture-cavity reservoirs. [ABSTRACT FROM AUTHOR]

During hydraulic fracturing, there is a temperature difference between the injected water and formation rock for shale gas wells. The objective of this study is to investigate how this temperature difference changes with time, and how it affects multiphase-flow modeling during the shut-in and flowback periods. We conducted numerical simulations to investigate the behaviors of fracture temperature in shale gas wells. The results show a significant increase in fracture temperature during the shut-in and flowback periods. Sensitivity analysis suggests that this temperature increase is strongly related to the thermal conductivity of formation rock, matrix permeability, and initial reservoir temperature. Simulation scenarios were further compared to investigate the effect of temperature on flowback data analysis. Without considering the thermal effect, flowback data analysis may yield an earlier fracture cleanup and overestimated fracture volume. In addition, this study suggests that the thermal effect may also have implications for optimizing flowback operations. [ABSTRACT FROM AUTHOR]