Gas Reservoir Model Research Articles

Optimal Design of Horizontal Well Cluster Spacing Based on Extended Finite Element and Numerical Simulation

As a crucial component of volumetric fracturing in unconventional oil and gas reservoirs, the design and optimization of cluster spacing significantly impact the morphology and production of fractures. Therefore, this paper establishes a multi-fracture propagation geological model based on the extended finite element method to study the scale and morphology of fracture propagation. Simultaneously, a gas reservoir model is established using CMG software, guided by production goals, and incorporating rock mechanics and physical parameters from region M to optimize cluster spacing design. The results indicate that smaller cluster spacing results in greater stress shadow effects, hindering the propagation of central fractures, and increasing the overlap of pressure drop zones, leading to possible repeated modifications during construction. Conversely, larger cluster spacing reduces stress shadow effects but may leave some areas between clusters unmodified, affecting production. Thus, through combined simulation optimization using both methods, a cluster spacing of 10-15 meters is recommended for region M, which has shown good on-site application results, significantly reducing the rate of repeated modifications.

Single Well Production Prediction Model of Gas Reservoir Based on CNN-BILSTM-AM

In the prediction of single-well production in gas reservoirs, the traditional empirical formula of gas reservoirs generally shows poor accuracy. In the process of machine learning training and prediction, the problems of small data volume and dirty data are often encountered. In order to overcome the above problems, a single-well production prediction model of gas reservoirs based on CNN-BILSTM-AM is proposed. The model is built by long-term and short-term memory neural networks, convolutional neural networks and attention modules. The input of the model includes the production of the previous period and its influencing factors. At the same time, the fitting production and error value of the traditional gas reservoir empirical formula are introduced to predict the future production data. The loss function is used to evaluate the deviation between the predicted data and the real data, and the Bayesian hyperparameter optimization algorithm is used to optimize the model structure and comprehensively improve the generalization ability of the model. Three single wells in the Daniudi D28 well area were selected as the database, and the CNN-BILSTM-AM model was used to predict the single-well production. The results show that compared with the prediction results of the convolutional neural network (CNN) model, long short-term memory neural network (LSTM) model and bidirectional long short-term memory neural network (BILSTM) model, the error of the CNN-BILSTM-AM model on the test set of three experimental wells is reduced by 6.2425%, 4.9522% and 3.0750% on average. It shows that on the basis of coupling the empirical formula of traditional gas reservoirs, the CNN-BILSTM-AM model meets the high-precision requirements for the single-well production prediction of gas reservoirs, which is of great significance to guide the efficient development of oil fields and ensure the safety of China’s energy strategy.

Numerical simulation of shale gas reservoir based on ILU-GMRES method

ABSTRACT The numerical simulation of shale gas reservoirs requires transforming mathematical models into large linear equation systems, and solving large linear equation systems requires a lot of time. A novel ILU-GMRES method for solving large linear equations is presented, which treats the sub matrix discretized at nodes as the basic elements of the coefficient matrix. By combining the incomplete LU decomposition method (ILU) with the generalized minimum residue method (GMRES), the discretized large linear equations are iteratively solved. A comparison was made between the new method and other methods for calculating the actual shale gas reservoir model. The results reveal that the new method has a faster calculation speed in solving linear equation systems. The calculation time of the novel ILU-GMRES method is 1029s, the calculation time of the generalized minimum residual method (GMRES) method is 2709s, the calculation time of the Gauss–Seidel method (GS) is 3786s, and the calculation time of the successive over relaxation method (SOR) method is 3386s, the calculation time of the preprocessing conjugate gradient method (PCG) is 3115s. The calculation speed of the novel method is almost 2.6 times faster than the GMRES method, the novel method is more effective in the numerical simulation of shale gas.

Sequential model identification with reversible jump ensemble data assimilation method

In data assimilation (DA) schemes, the form representing the processes in the evolution models are pre-determined except some parameters to be estimated. In some applications, such as the contaminant solute transport model and the gas reservoir model, the modes in the equations within the evolution model cannot be predetermined from the outset and may change with the time. We propose a framework of sequential DA method named Reversible Jump Ensemble Filter (RJEnF) to identify the governing modes of the evolution model over time. The main idea is to introduce the Reversible Jump Markov Chain Monte Carlo (RJMCMC) method to the DA schemes to fit the situation where the modes of the evolution model are unknown and the dimension of the parameters is changing. Our framework allows us to identify the modes in the evolution model and their changes, as well as estimate the parameters and states of the dynamic system. Numerical experiments are conducted and the results show that our framework can effectively identify the underlying evolution models and increase the predictive accuracy of DA methods.

Productivity Model Study of Water-Bearing Tight Gas Reservoirs Considering Micro- to Nano-Scale Effects

Tight sandstone is rich in micron- and nano-scale pores, making the two-phase flow of gas and water complex. Establishing reliable relative permeability and productivity models is an urgent issue. In this study, we first used a slip model to correct the gas phase’s no-slip Hagen–Poiseuille equation for nano- and micropores. Then, combined with the fractal theory of porous media and the tortuous capillary bundle model, we established two-phase relative permeability models for nanopores and micropores. These relative permeability models comprehensively consider the gas slippage effect, the initiation pressure gradient, the pores’ fractal characteristics, and water film mechanisms. Based on these models, we developed a three-region coupling productivity model for water-bearing tight gas reservoirs with multi-stage fractured horizontal wells. This productivity model considered the micro- and nano-scale effects and the heterogeneity of fracture networks. Then, the model was solved and validated with a field case. The results indicated that the three-region composite unsteady productivity model for water-bearing tight gas reservoirs, which incorporated micro- and nano-scale effects (with consideration of micro-scale and nano-scale phenomena in the fluid flow), could accurately predict a gas well’s productivity. An analysis of the factors influencing productivity showed that ignoring the micro- and nano-scale effects in water-bearing tight gas reservoirs will underestimate the reservoir’s productivity. The initial water saturation, the two-phase flow’s initiation pressure gradient, and capillary force are all negatively correlated with the productivity of gas wells, while the conductivity of the fractures is positively correlated with gas well productivity.

Mixing dynamics and recovery factor during hydrogen storage in depleted gas reservoirs

Large-scale hydrogen storage is strategically important for society and depleted gas reservoirs have been proposed as a potential solution. However, the mixing with remaining hydrocarbon gas during injection/production cycles and the impact of different reservoir parameters on the hydrogen recovery factor (RFH2) have not been fully understood. We investigate mixing dynamics and analyze the effects of initial hydrocarbon recovery factor, reservoir permeability, well perforation length, intelligent completion, and fractures on RFH2. Fine-grid gas reservoir models with compositional simulation were used to simulate cyclic hydrogen storage. Mixing of injected hydrogen with remaining hydrocarbon gas occurred in three distinct phases in each cycle: 1) displacement of remaining hydrocarbon gas through pressure-driven flow during hydrogen injection, 2) density-driven flow of gases during the idle time after hydrogen injection, and 3) pressure-driven flow of gases towards the production intervals during the hydrogen production phase. Higher RFH2 s were obtained when the storage process was initiated at higher hydrocarbon gas recovery factors. Storing hydrogen in reservoirs with lower permeability also led to higher RFH2 s, provided the well pressure limits were not an issue. In conditions of a 5× to 15× increase in permeability, the injected hydrogen moved upward and spread laterally, positioning it farther from the wellbore. This made hydrogen production more difficult and placed the mixing zone and hydrocarbon gas closer to perforations. Shorter perforation lengths at the top of the formation resulted in the best RFH2 s. Additionally, intelligent completions (that closed perforations producing gas with low hydrogen content) improved RFH2 by providing the possibility of purer hydrogen production. The presence of natural fractures significantly reduced hydrogen recovery, especially in the first few cycles. However, the influence decreased over time as highly conductive flow paths provided by fractures can contribute to the production of the accumulated unrecovered hydrogen from previous cycles.

Characteristics and an accumulation model of a bauxite gas reservoir in the southwestern Ordos Basin

A significant breakthrough has been made in natural gas exploration in the aluminum (Al)-bearing rock series of the Permo-Carboniferous System in the Longdong (LD) region of the Ordos Basin, and this has sparked great interest in studying bauxite reservoirs within the oil and gas industry. Although recent research has focused on the depositional environment and reservoir well logging identification, there is still a lack of understanding regarding the characteristics, formation mechanism, and accumulation model of bauxite gas reservoirs. This knowledge gap hinders the rapid exploration of this new type of gas reservoir. Based on core observations, major and trace element analyses, whole-rock X-ray diffraction, thin section examination, and scanning electron microscopy (SEM), the pore types, physical properties, reservoir formation mechanisms and accumulation models of the bauxite reservoirs were determined. The results are as follows: (1) The main mineral components of the Al-bearing rock series are diaspore and clay minerals. The bauxite that formed by the weathering, leaching, sedimentation and diagenesis of the parent rock has a high diaspore content and secondary dissolution pores. (2) Bauxite with a high aluminum content has a high porosity and permeability and can be used as a potential natural gas reservoir, and the reservoir space is mainly composed of dissolution pores. There is a strong correlation between the aluminum content and porosity, indicating that high Al2O3 or diaspore contents can serve as reliable indicators for an effective reservoir. (3) The overlying coal-bearing source rocks and the underlying karst are key to bauxite reservoir formation. The concurrent presence longitudinally of coal, bauxite, fractures, and karst collapse offers valuable guidance for the exploration of natural gas in bauxite within the Ordos Basin. These findings have significant implications for natural gas exploration in Al-bearing rocks in North China and other regions.

Study on Water Intrusion Flow Model of the Tight Gas Reservoir

Study on Water Intrusion Flow Model of the Tight Gas Reservoir

Reservoir Characteristics and Formation Model of the Bauxite Gas Reservoir: The Benxi Formation in the LX Block, Northeast of Ordos Basin, China.

Recently, horizontal well L47-1CH in the Longdong area of the southwestern Ordos Basin made a significant breakthrough in bauxite natural gas exploration, changing the traditional geological understanding that bauxite could not form effective reservoirs. To further explore the exploration and development potential of bauxite natural gas reservoirs in the northeast of the Ordos Basin, it is urgent to carry out basic geological studies. This paper discusses the sedimentary environment, reservoir characteristics, and formation patterns of the bauxite gas reservoirs in the LX Block using trace elements, thin sections, X-ray diffraction, scanning electron microscopy, conventional physical properties, constant pressure mercury, etc. Then, the distribution pattern of bauxite was studied according to the restoration of the karst paleogeomorphology, and the formation model of bauxite was ultimately established. The results show that bauxite developed a clear triple-segment structure vertically, characterized by rich iron at the bottom, high aluminum at the middle, and low iron at the top. The mineral composition of the bauxite section mainly includes diaspore, iron minerals, titanium minerals, and birnessite. The types of pores mainly include intra- and intergranular dissolved pores, matrix-dissolved pores, intercrystalline pores, and microfractures. The porosity ranges from 1.51 to 9.90%, with a relatively good sorting and connectivity of the pore and throat. The bauxite was formed in a hot and humid climate, deposited in a shallow-water tidal flat and lagoon sedimentary environment with oxygen depleted, and experienced oscillatory regression during the deposition process. The thickness of bauxite is significantly controlled by karst paleogeomorphology, and it is mainly distributed at the negative terrain positions of karat pits and karst terraces. The above results can provide a geological basis for the exploration and development of bauxite in the Ordos Basin and similar basins worldwide.

Three-Water Differential Parallel Conductivity Saturation Model of Low-Permeability Tight Oil and Gas Reservoirs

Addressing the poor performance of existing logging saturation models in low-permeability tight sandstone reservoirs and the challenges in determining model parameters, this study investigates the pore structure and fluid occurrence state of such reservoirs through petrophysical experiments and digital rock visualization simulations. The aim is to uncover new insights into fluid occurrence state and electrical conduction properties and subsequently develop a low-permeability tight sandstone reservoir saturation model with easily determinable parameters. This model is suitable for practical oilfield exploration and development applications with high evaluation accuracy. The research findings reveal that such reservoirs comprise three types of formation water: strongly bound water, weakly bound water, and free water. These types are found in non-connected micropores, poorly connected mesopores where fluid flow occurs when the pressure differential exceeds the critical value, and well-connected macropores. Furthermore, the three types of formation water demonstrate variations in their electrical conduction contributions. By inversely solving rock electrical experiment data, it was determined that for a single sample, the overall cementation index is the highest, followed by the cementation index of pore throats containing strongly bound water, and the lowest for the pore throats with free water. Building on the aforementioned insights, this study develops a parallel electrical pore cementation index term, ϕm′, to account for the differences among the three types of water and introduces a parallel electrical saturation model suitable for logging evaluation of low-permeability tight oil and gas reservoirs. This model demonstrated positive application effects in the logging evaluation of low-permeability tight gas reservoirs in a specific basin in the Chinese offshore area, thereby confirming the advantages of its application.

A comparative analysis of gas mixing during the underground hydrogen storage in a conventional and fractured reservoir

Climate change and political tensions are reducing the time for the energy transition. Large-scale underground hydrogen storage (UHS) can be crucial in future energy systems for decarbonizing the world's economy as well as ensuring energy security. There are challenges, however, that prevent it from being used on large scale as an energy carrier. The high cost of hydrogen cushion gas is one of them. It is not economical that a portion of hydrogen remains in a reservoir as a cushion gas during UHS until the end of a storage operation. Consequently, inert gases such as nitrogen can be used as cushion gas. Hydrogen's heating value gets reduced, however, due to gas mixing. Since gas mixing behavior differs in reservoirs with different mechanisms, hydrogen heating value was employed to examine the gas mixing behavior during UHS in conventional and fractured reservoir models (dual-porosity) for the first time in this study. The mixing behavior of hydrogen gas with replaced cushion gas will first be examined in the absence and presence of diffusion using a conventional gas reservoir model. Then some reservoir and operational parameters will be investigated in order to determine how they affect the gas mixing behavior, including reservoir porosity, permeability, rock compressibility, and cushion gas type. Next, a basic UHS scenario with dual-porosity will be examined to determine how hydrogen gas and cushion gas mix in the presence and absence of diffusion and the effects of specific parameters on gas mixing behavior in the fractured reservoir (NFR) model, including matrix-fracture transmissibility and cushion gas type. According to the results, in the conventional reservoir model, considering diffusion during early hydrogen production results in a decrease in hydrogen heating value. While in the second stage of hydrogen production, diffusion increases the hydrogen heating value, resulting from the sweeping effect. Dual-porosity models illustrate the opposite behavior. As well, porosity reduction resulted in higher hydrogen heating values during early production but reversed during late production. Unlike the effect of rock compressibility on heating value of hydrogen, a lower hydrogen heating value was obtained during hydrogen production as the reservoir permeability increased. Also, carbon dioxide cushion gas showed reversed effect on gas mixing during UHS in the conventional compared to the NFR case.

Improving Gas Recovery of Water Drive Gas Reservoir

A gas reservoir with bottom water drive has lower recovery factor compared to depletion drive gas reservoir. Along with the increase in gas demand and the majority of gas reservoirs are water-drive, a method that are still being developed to increase the recovey factor in water-drive gas reservoir is co-production method. This method reducing water influx by planned water production. In this study, a conceptual model of gas reservoir with depletion-drive and water-drive is build and being analyzed. Co-production technique is applied by adding one water production well to the water-drive gas reservoir. The recovery factor is being analyzed through some production scenarios. Sensitivity analysis are being done with parameters including: reservoir permeability, permeability anisotropy, aquifer volume, flow rate of water production, gas tubing head pressure, and gas well perforation interval Furthermore, experimental design, response surface methodology, and monte carlo simulation is used to analyze the influencing parameter of gas recovery factor. It is found from this study that co production increased gas recovery factor by 28% from water drive gas reservoir, with water production rate is the most influencing parameter.

Q-compensated wavefield depth extrapolation-based migration using a viscoacoustic wave equation

In a viscoacoustic medium, intrinsic attenuation causes seismic wavefields to attenuate in amplitude and become dispersed in phase, leading to distorted structural imaging and inaccurate migrated amplitudes. To address this problem, viscoacoustic reverse time migration corrects for dispersion and amplitude attenuation effects in wavefield propagation in forward and backward directions. To provide a parallel alternative approach, the time fractional derivative viscoacoustic wave equation in the depth domain is solved and a Q-compensated wavefield depth extrapolation scheme is established to compensate for viscoacoustic effects during recursive wavefield depth extrapolation. This approach decouples the amplitude attenuation and phase dispersion effects from the viscoacoustic vertical wavenumber. To suppress high wavenumber components and address the problem of exponential amplitude growth during wavefield depth extrapolation, we limit the imaginary part of the vertical wavenumber in the frequency wavenumber domain and use an adaptive stabilization solution. Numerical experiments of impulse responses in a viscoacoustic isotropic medium demonstrate that our proposed scheme can observe calculated wavefields exhibiting amplitude attenuation and phase dispersion effects in comparison to wavefields of the acoustic medium, indicating good agreement with theoretical expectations. We also demonstrate the capability of our proposed scheme to recover imaging amplitudes through a variety of numerical experiments, such as imaging of three-layer, Marmousi, and BP gas reservoir models. The results indicate that our proposed scheme can recover amplitude attenuation and phase dispersion effects more accurately than acoustic migration. We also use marine seismic data featuring natural gas hydrates to indicate that our proposed Q-compensated scheme can generate an enhanced imaging result, especially for the bottom simulating reflectors, compared with the conventional imaging algorithm without Q-compensation.

A numerical study of complex fractures propagation path in naturally fractured gas shale: Reorientation, deflection and convergence

Shale gas reservoir is characterized as the naturally fractured formation, which is benefit for complex hydraulic fracture network generation. The propagation path is crucial to determine the reservoir stimulation result, and evaluate the quality of complex hydraulic fracture network. To investigate the propagation path of complex hydraulic fracture in gas shale, the hybrid combined discrete fracture network-finite element method (DFN-FEM) model is involved. Combining a linear hardening and a non-linear softening process, a non-linear traction-separation law is proposed to describe the fracture damage evolution. Validated with open-reported laboratory experiments, the hydraulic-natural fracture (HF–NF) interaction criterion is depicted under four geomechanical and injection factors. Based on a field-scale model of Sichuan basin shale gas reservoir, the complex hydraulic fractures propagation process is simulated with rock deformation and stress shadow. Several propagation path indexes are defined with fracture morphology to discuss the effect of representative geomechanical, injection and multi-clustering parameters. The results show that the tension fractures are predominant to hydraulic fractures propagation path and shear the natural fractures, due to the combined influence of natural fractures network and interference between clusters. The horizontal stress contrast and the injection fluid viscosity is governing to the propagation path and morphology, rather than the friction coefficient and injection rate. Multi-clustered hydraulic fractures converge into a dominant fracture due to the attraction with a short clusters-spacing, while the exclusion is observed along the propagation path with the increase of clusters number.

Grounded source transient electromagnetic 3D forward modeling with the spectral-element method and its application in hydraulic fracturing monitoring

A long wire with large current source transient electromagnetic (TEM) monitoring, with a large detection depth, low cost, safety, and environmental protection, has unique advantages in the testing and identification of unconventional reservoir fluid and the evaluation of stimulated reservoir volume. So, the TEM 3D forward modeling method has become a research hotspot. Although the finite-element method (FEM) is a type of numerical algorithm that has been widely applied in three-dimensional (3D) electromagnetic field forward modeling, the efficiency and accuracy of FEM require further improvement in order to meet the demand of fast 3D inversion. By increasing the order of the basis function and adjusting the principle of mesh discretization, the precision of the mixed-order spectral-element (SEM) result will be increased. The backward Euler scheme is an unconditionally stable technique which can ignore the impact of the scale of the time step. To achieve a better description of the nonlinear electromagnetic (EM) response of the grounded source TEM method and to optimize the efficiency and accuracy/precision of the 3D TEM forward modeling method significantly, we proposed the use of 3D TEM forward modeling based on the mixed-order SEM and the backward Euler scheme, which can obtain more accurate EM results with fewer degrees of freedom. To check its accuracy and efficiency, the 1D and 3D layered models are applied to compare the SEM results with the semi-analytical and FEM solutions. In addition, we analyzed the accuracy and efficiency of the SEM method for different types of order basis functions. Finally, we calculated the long-wire source TEM response for a practical 3D earth model of a shale gas reservoir for fracturing monitoring and tested the feasibility of the TEM method in a hydraulic fracturing monitoring area to further demonstrate the flexibility of the SEM method.

Fracture Modeling of Deep Tight Sandstone Fault-Fracture Reservoir Based on Geological Model and Seismic Attributes: A Case Study on Xu 2 Member in Western Sichuan Depression, Sichuan Basin

With significant geological reserves and high resource abundance, the Xujiahe Formation in the Western Sichuan Depression is considered a key target for natural gas exploration and development in continental clastic rocks within the Sichuan Basin. However, this formation remains underdeveloped. Critical to forming “sweet spots” of tight reservoir is the presence of fractures. Based on available data sources, including core samples, well logs, and outcrop data, we utilized a combination of geophysical and geological modeling techniques to clarify the characteristics of effective fractures in tight gas reservoirs. This allowed us to construct a geological model of a tight sandstone fault-fracture gas reservoir in the Xu 2 Member of the Xujiahe Formation located in the Xinchang area, which represents a fault-fracture reservoir formed by high-angle faulting-derived fractures and controlled by the S-N trending fault. With this model, a variety of seismic attributes, including likelihood and entropy, was used to predict the fault-fracture reservoir. Furthermore, geological information, well logs, and seismic attributes were integrated for characterizing the fractures of different scales. The cutoff on various attributes for characterizing the fault-fracture reservoir was defined, and the distribution of the fault-fracture reservoir was delineated. By using the geological modeling technique, the fracture model of the fault-fracture reservoir comprising natural fractures at different scales was built. This model provides further guidance for the exploration and development of the Xu 2 Member tight gas reservoirs in the Xinchang area and, as demonstrated by drilling results, has achieved remarkable effects in practice. This approach has shown good performance in characterizing fracture models. However, due to the complexity of fractures and the discrepancy between the scale of fractures and the scale that can be predicted by geophysical methods, there may still be some uncertainties associated with this method.

Optimization of wellbore multiphase pipe flow calculation model for low permeability sandstone gas reservoir in Ordos Basin

The study of wellbore vertical pipe flow is the basis of reasonable production allocation and wellbore size optimization. According to the characteristics of low water gas ratio in sandstone gas reservoir of a gas field in Ordos Basin, the bottom hole pressure of typical gas wells in this area is calculated by using various wellbore pipe flow models such as Hagedorn brown, beggs Brill, Mukherjee Brill, gray and Aziz; Based on the measured bottom hole pressure, the relative performance coefficient evaluation method is used to optimize the wellbore calculation method. The results show that for the sandstone gas reservoir with low water gas ratio in gas field a, the calculation results of Hagedorn Brown model are in good agreement with the test results, so it is appropriate to use the Hagedorn Brown model to calculate the vertical pipe flow characteristics.

Apparent permeability in tight gas reservoirs combining rarefied gas flow in a microtube

In tight gas reservoirs, the major flow channels are composed of micro/nanopores in which the rarefaction effect is prominent and the traditional Darcy law is not appropriate for gas flow. By combining the Maxwell first-order slip boundary condition and Navier–Stokes equations, a three-dimensional (3D) analysis of compressible gas slip flow in a microtube was presented, and the flux rate and pressure variation in the flow direction were discussed. Subsequently, by superimposing the Knudsen diffusion, a gas flux formula applicable to a larger Knudsen number was further proposed and satisfactorily verified by two groups of published experimental data in microtubes or microchannels in the membrane. The results indicate that slip flow and Knudsen diffusion make an important contribution to the total gas flow in the microtube, and their weight increases with an increase in the Knudsen number. By substituting the gas flux formula into Darcy’s law for compressible gas, a new apparent permeability model for tight gas reservoirs was proposed, in which the slippage effect and Knudsen diffusion were synthetically considered. The results indicate that the apparent permeability of tight reservoirs strongly depends on the reservoir pressure and pore-throat radius, and an underestimation value may be predicted by the previously published models. This study provides a case study for evaluating these apparent permeability models, which remains a challenging task in the laboratory.

Rapid productivity prediction method for frac hits affected wells based on gas reservoir numerical simulation and probability method

Abstract As an important unconventional resource, shale gas can alleviate energy shortage, and its efficient development ensures the long-term growth of oil and gas. The prediction of production levels and estimated ultimate recovery with high accuracy is necessary for shale gas development. Conventional methods are widely applied in the oil and gas industry owing to their simplicity and effectiveness; however, none of them can accurately predict the results for frac hits affected wells. In this work, a probability method based on the numerical model of shale gas reservoir has been formed. In view of the impact of frac hits on the productivity of production wells during the development of shale gas reservoirs, an embedded discrete fractured numerical simulation method for gas reservoirs is proposed to simulate the geological engineering parameter range of wells before frac. And aiming at the established numerical model of shale gas reservoir, this method adopts the ensemble smoother with multiple data assimilation automatic history matching technology to carry out the history matching process of the model. Based on the probability theory and numerical simulation results, this study analyses the influence of different distribution functions of parameters on the calculation results of reserves, and obtains the expected curve of reserves through combination calculation. Besides, the effectiveness of this method was verified by comparing with other traditional predicted method.

Role of gas multiple transport mechanisms and fracture network heterogeneity on the performance of hydraulic fractured multiwell-pad in unconventional reservoirs

The hydraulic fractured multiwell-pad (HFMP) is gradually adopted as an efficient way to enhance shale gas recovery in shale reservoirs. Microseismic evidence supports that the fracture network heterogeneity can be expected in the overlap region initiated by multi-well fracturing. However, most modeling studies have focused on a single well, neglecting the enhanced stimulated reservoir volume (ESRV) between adjacent wells and the associated well interference. In this research, a novel semi-analytical solution for a shale gas reservoir model coupling fracture network heterogeneity and gas multiple transport mechanisms is derived. The proposed model can capture the gas desorption, diffusion, and viscous flow in matrix and gas viscous flow in fracture system as well as the properties of ESRV and SRV. The bottom-hole pressure (BHP) and production rate dynamics illustrate that the HFMP in a shale reservoir with ESRV and SRV apparently differs from the common single well model in the shale reservoir with homogeneous fracture network. Eight flow regimes can be recognized during shale gas development: wellbore storage flow, short-term transition flow, the first linear flow perpendicular to hydraulic fractures (HFs), the first radial flow around HFs, the second linear flow beyond the tip of HFs, the second radial flow in SRV region, transition flow, and the third radial flow regimes in USRV. Sensitive analyses demonstrate that ESRV permeability, well spacing, SRV size and permeability, and production rate difference between adjacent wells all exhibit significant effects on BHP and production rate performances. The findings obtained in this research shed light on the proper consideration of fracture network heterogeneity and gas viscous flow in shale matrix for reservoir evaluation and development.