Fractured Reservoir Model Research Articles

Comparative Study on Artificial Fracture Modeling Schemes in Tight Reservoirs—For Enhancing the Production Efficiency of Tight Oil and Gas

In order to improve the reliability of the deployment of production schemes after artificial fracturing in tight reservoirs, it is urgent to carry out research on the description of fractures after artificial fracturing. In this study, taking the Chang 61 oil formation group in the Wangyao South area of Ordos Basin as an example, three different fracture modeling schemes are used to establish the geological model of fractured reservoirs, and the fitting ratios of the respective reservoir models are calculated by using the method of reservoir numerical simulation of the initial fitting, and the optimal fractured reservoir modeling scheme is screened in the end. The research area adopts three types of fracture prediction results based on FMI fracture interpretation data, seismic fracture prediction data, and rock mechanics artificial fracturing simulation data. On this basis, geological models of fractured reservoirs are established, respectively. The initial fitting of reservoir values of each geological model are compared, and the highest initial fitting rate of reservoir values is 88.44%, which is based on rock mechanics artificial fracturing simulation data. However, the initial fitting rate of the reservoir model was the lowest at 75.76%, which was established based on the fracture random modeling results of FMl fracture interpretation data. Under the constraints of seismic geostress prediction results and microseismic monitoring data, the simulation results of rock mechanics artificial fracturing fracture are used as the basis, on which the geological model of artificially fractured reservoirs is thus established, and this scheme can more realistically characterize the characteristics of fractured reservoirs after artificial fracturing in the study area.

Research Progress of Three-dimensional Geological Modeling and Multi-field Coupling of Fractured Oil and Gas Reservoirs

Fractured oil and gas reservoirs play an important role in oil and gas exploration and development due to their complex fracture network structure. As the main fluid channel in the reservoir, fractures have a significant impact on the migration, accumulation and exploitation efficiency of oil and gas. This paper summarizes the key geological characteristics of fractured reservoirs, including fracture types, distribution rules and main controlling factors of fracture development, and discusses the influence of fractures on reservoir physical properties. Furthermore, the deterministic and stochastic modeling methods of three-dimensional geological modeling of fractured reservoirs and the latest progress of discrete fracture network modeling technology are introduced in detail. In addition, this paper also discusses in detail the application of multi-field coupling model in the numerical simulation of fluid flow in fractured reservoirs, including continuous medium model and discrete medium model, and their advantages and disadvantages in simulating fluid flow in fractured reservoirs. Finally, this paper summarizes the research progress of multi-physics coupling model of fractured reservoirs, and points out the direction and challenges of future research. Through these studies, it can provide theoretical support and technical guidance for oil and gas exploration and development, in order to achieve more effective development and management of fractured reservoirs.

Resurgent dome and super-hot enhanced geothermal system: The Sahinkalesi Massif within the Hasandag Stratovolcanic Province, Central Anatolia, Turkey

The Sahinkalesi, a volcanic dome located NNE of Hasandağ, Türkiye exhibits anomalous heat flow value, geothermal gradient and the Curie point depth is located at very shallow depth in this region. Our investigation indicates presence of super-critical thermal regime (378°C) at about 4 km depth and the MT analysis indicate shallow magma chamber at about 5 km depth. The crust is relatively thin below this region with the low-velocity region located at depth of about 36 km. Thermo-Hydro-mechanical model investigation has been carried out using finite element discretization technique. For faulted zone reservoir models, 30 years of geothermal energy exploitation does not cause thermal breakthrough for mass flow rates up to 500 kg/s, however, the mean stress developed in the reservoir becomes much larger and may be unsustainable for the reservoir stability. To ensure the success of a fractured reservoir model, the use of multiple wellbores is recommended. In the case of a closed-loop geothermal system, the primary concern is the control of thermoelastic stress. This can be achieved either by increasing the wellbore depth while reducing the injection mass flow rate, or by extending the wellbore's horizontal component. The outlet temperature in both the cases maintained at 275°C. This is the first time a superhot EGS site has been identified in Türkiye.

Shear wave velocity prediction for fractured limestone reservoirs based on artificial neural network

AbstractShear wave velocity is an essential parameter in reservoir characterization and evaluation, fluid identification and prestack inversion. However, conventional data‐driven or model‐driven shear wave velocity prediction methods exhibit several limitations, such as lack of training data sets, poor model generalization and weak model robustness. In this study, a model‐ and data‐driven approach is presented to facilitate the solution of these problems. We develop a theoretical rock physics model for fractured limestone reservoirs and then use the model to generate synthetic data that incorporates geological and geophysical knowledge. The synthetic data with random noise is utilized as the training data set for the artificial neural network, and a well‐trained shear wave velocity prediction model, random noise shear wave velocity prediction neural network, is established by parameter tuning, which fits the synthetic data with noise well. The neural network is applied directly to the real field area. Compared with conventional shear wave prediction methods, such as empirical formulas and the improved Xu–White model, the prediction results show that the random noise shear wave velocity prediction neural network has better prediction performance and generalization. Furthermore, the prediction results demonstrate the efficacy of the proposed approach, and the approach has the potential to perform shear wave velocity prediction in real areas where training data sets are unavailable.

Modelling of water injection-induced shear stimulation and heat extraction in hot fractured reservoirs

Hydroshearing has been proposed as an effective technique for enhancing the permeability of fractured geothermal reservoirs. This approach involves complicated thermo-hydro-mechanical (THM) coupling, but the shear behaviour and its effect on flow and heat transfer are often simplified. In this study, Barton–Bandis (BB) joint behaviour is extended to include nonlinear rock joint deformation, shear dilation and post peak softening and healing behaviours. Two models of field-scale fractured geothermal reservoirs are considered. In addition, the widely used Mohr-Coulomb (MC) model is also incorporated into the THM coupled model for comparison. The results show that cold water injection-induced high-temperature rock contraction and fluid pressure increase, reducing the effective stress and promoting fracture shear deformation and irreversible slip. Moreover, shear dilation, shear softening, and nonlinear fracture opening notably alter reservoir permeability. The two models exhibit entirely different behaviours due to different pathway evolutions and consequent pressure build-up. The BB model displays a larger shear disturbance zone than the MC model, significantly enhancing the permeability and heat extraction within the fractured reservoirs. Accurate descriptions of the mechanical behaviour of rock fractures in hydroshearing models are crucial, suggesting the potential of these models to enhance fractured reservoirs and regulate fracturing for improved geothermal heat extraction.

Response characteristics and novel understandings of dual induction logging of horizontal wells in fractured reservoirs

Previous studies commonly used dual laterolog or induction logging in vertical wells to study fractured reservoirs. However, there are few studies about the response characteristics of dual induction logging of horizontal wells in fractured reservoirs, which interferes with the evaluation of horizontal wells in fractured reservoirs. In this study, firstly, the finite element method is used to establish the fractured reservoir model and the dual induction instrument of horizontal well. Then, the response characteristics of dual induction logging in fractured reservoirs with different fracture conductivity, fracture dip angle, fracture width and fracture length are simulated and analyzed. The results show the response characteristics as follows: (1) The apparent conductivity of dual induction logging increases first and then decreases along with the increase of fracture conductivity, when the fracture conductivity is lower than formation conductivity, the apparent conductivity is similar to formation conductivity; (2) The fracture dip angle has little effect on the apparent conductivity of induction logging, when the fracture conductivity is high, the apparent conductivity decreases with the increase of the fracture dip angle; (3) The effect of fracture width and fracture length on apparent conductivity is similar. The larger the fracture width or length, the greater their influence on the apparent conductivity, which is different from the response characteristics of laterologs. In applications, these characteristics can be demonstrated by two wells in the southwest Ordos Basin, China. Finally, advantages and disadvantages of the simulation method, applications, logging responses discussed in detail, as well as the response characteristics and the shielding effect of fractures on electromagnetic waves of dual induction instrument are discussed in detail. The applications and discussions show that this study can provide response characteristics and novel understandings for the evaluations of horizontal wells in fractured reservoirs, especially in areas where dual induction logging is widely used.

A new rock physics model for fractured oil shale reservoirs in Mahu oil field

The exploration of unconventional reservoirs such as oil shale has become a focus of research in the oil/gas industry, but due to the diversity of lithology and structural complexity of shale reservoirs, the study of their rock physics laws is a challenge. By analyzing the physical, lithologic, and fluid characteristics of oil shale reservoirs in the Mahu area of Xinjiang, China, we adopted a variety of effective-medium theories to carry out rock physics modeling. We analyzed the differences in the calculation results of various theoretical models, and finally constructed a set of rock physics modeling processes suitable for oil shale reservoirs. The analysis shows that the calculation results of Voigt-Reuss-Hill (VRH) and Hashin-Shtrikman (HS) average for mixed mineral matrix are very similar, but there are certain differences between the upper and lower bounds calculated by them. The upper and lower bounds of HS average are closer than VRH average. We used the Kuster-Toksoz effective-medium, differential effective-medium (DEM), and self-consistent approximation models to construct the rock skeleton and analyzed the differences of the models. The results of the three models are almost identical, but their assumptions and limitations differ. We used DEM in the final shale model, considering the large porosity and the order of inclusion filling. According to the fracture distribution characteristics of oil shale reservoirs, we used an inclined fracture model to describe the fractures with different structural characteristics. Finally, the established shale rock physics model was used to calculate the actual logging data, and the results of elastic parameters are consistent with the measured data. Through the inversion of the fracture parameters, the inversion results are consistent with the measured results as a whole, indicating that the model has certain applicability to the simulation of oil shale reservoirs.

Deep Graph Learning-Based Surrogate Model for Inverse Modeling of Fractured Reservoirs

Inverse modeling can estimate uncertain parameters in subsurface reservoirs and provide reliable numerical models for reservoir development and management. The traditional simulation-based inversion method usually requires numerous numerical simulations, which is time-consuming. Recently, deep learning-based surrogate models have been widely studied as an alternative to numerical simulation, which can significantly improve the solving efficiency of inversion. However, for reservoirs with complex fracture distribution, constructing the surrogate model of numerical simulation presents a significant challenge. In this work, we present a deep graph learning-based surrogate model for inverse modeling of fractured reservoirs. Specifically, the proposed surrogate model integrates the graph attention mechanisms to extract features of fracture network in reservoirs. The graph learning can retain the discrete characteristics and structural information of the fracture network. The extracted features are subsequently integrated with a multi-layer recurrent neural network model to predict the production dynamics of wells. A surrogate-based inverse modeling workflow is then developed by combining the surrogate model with the differential evolutionary algorithm. Numerical studies performed on a synthetic naturally fractured reservoir model with multi-scale fractures illustrate the performance of the proposed methods. The results demonstrate that the proposed surrogate model exhibits promising generalization performance of production prediction. Compared with tens of thousands of numerical simulations required by the simulation-based inverse modeling method, the proposed surrogate-based method only requires 1000 to 1500 numerical simulations, and the solution efficiency can be improved by ten times.

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.

Thermal‒hydraulic‒mechanical‒chemical coupling analysis of enhanced geothermal systems based on an embedded discrete fracture model

Enhanced geothermal system (EGS) is subject to the comprehensive effects of multiple physical fields during the long-term heat extraction process, including hydraulic (H), thermal (T), mechanical (M) and chemical (C) fields. The embedded discrete fracture model (EDFM) can effectively simulate the variations of flow, temperature, mechanical and concentration fields in fractured reservoirs. At present, however, the thermo-hydro-mechanical-chemical (THMC) coupling model based on EDFM is less researched. In this paper, the THMC coupling model of fractured reservoir is established based on EDFM by considering the changes in reservoir heterogeneity and physical properties as well as water–rock reactions. Then, the spatiotemporal evolution of flow, temperature, displacement and concentration fields in the operation process of EGS is simulated and analyzed. And the following research results are obtained. First, when the permeability of the basement rock is low, the production temperature decrease during exploitation is gradual, allowing EGS to maintain a high exploitation temperature for an extended period. However, lower permeability may result in a decrease in the quality flow rate from production wells, thereby affecting net heat extraction power. Second, when fracture permeability or fracture opening changes, EGS can output higher temperature stably for a certain period and then the temperature decreases at different amplitudes. When the fracture permeability increases to a certain value or the fracture opening decreases to a certain value, the influence of the change in fracture parameters on production temperature gets weak. Third, After 40 years of EGS operation, considering variable property fluids results in a 22 °C lower exploitation temperature compared to using constant property fluids, and considering water–rock reactions results in a 15 °C lower exploitation temperature, with a 12.5 % increase in reservoir average porosity. In conclusion, when researching a long-term operating EGS, it is necessary to comprehensively consider the influences of reservoir rock parameters, physical properties of injected fluid, water–rock reaction and other factors. And in the future, attention shall be paid to the two-way coupling of chemical reaction and mechanical deformation of other mineral compositions in the reservoir to the hydro-thermo-chemical field influence, so as to provide more accurate and reliable prediction for the engineering development and utilization of EGS reservoirs.

Research Progress of Drilling and Completion Fluid Loss Model in Fractured Reservoir

Well loss and its accompanying reservoir damage is a common and serious problem, which not only greatly restricts the economic benefit, but also seriously affects the correct evaluation of reservoir oil and gas resources in the early stage of exploration. With the exploration and development of deep Marine carbonate oil and gas resources, fracture leakage has gradually become a frontier and hot issue to be studied urgently. Foreign scholars began to study the leakage model of fractured reservoir in the 1990s, but at present, domestic scholars mainly focus on the clastic rock model, focusing on the plugging technology and plugging materials, while ignoring the importance of the dynamic development of the leakage indirectly reflecting the leakage type and the size of the leakage channel. This paper comprehensively analyses the effects of drilling completion fluid rheology, fracture opening variation, fracture wall filtration and other factors on well loss from the time sequence of the establishment of the leakage model, summarizes the research progress of the mathematical model of leakage in fractured reservoirs, and proposes to pay attention to and strengthen the monitoring of the leakage mechanism and the dynamic process of leakage, so as to provide a theoretical basis for the rapid diagnosis of leakage types and the optimization of leakage control.

3D geological modeling of deep fractured low porosity sandstone gas reservoir in the Kuqa Depression, Tarim Basin

The fractured reservoir is one of the significant petroleum reservoir types in China, representing over one-third of total reserves. The Kuqa Depression in the Tarim Basin is dominated by fractured low-porosity sandstone gas reservoirs with characteristic tight matrix, developed fractures, and edge and bottom water. However, the continued development of these reservoirs has led to various problems, including strong reservoir heterogeneity, low well control, complex gas-water relationships, and early water invasion. Addressing these issues requires a detailed understanding of the reservoir’s geological characteristics. One method for achieving a fine reservoir description is through the use of 3D geological modeling. This high-level, comprehensive characterization technique is widely used throughout the entire life cycle of oil and gas field development. A 3D geological model can accurately predict the actual underground reservoir characteristics and provide a geological basis for later numerical simulation work. Based on a study of the geological characteristics of the Kuqa Depression in the Tarim Basin, a 3D geological modeling technique was developed, which includes structural modeling, facies modeling, petrophysical modeling, and fracture modeling. This technology has been successfully applied to many deep gas reservoirs in the Kuqa Depression of the Tarim Basin, leading to enhanced gas recovery.

A Numerical Model for Pressure Analysis of a Well in Unconventional Fractured Reservoirs

Fractured reservoirs are highly heterogeneous in both matrix and fracture properties, which results in significant variations in well production. Assessing and quantifying the influence of fractures on fluid flow is essential for developing unconventional reservoirs. The complicated effects of fractures in unconventional fractured reservoirs on fluid flow highly depend on fracture geometry, fracture distribution, and fracture properties, which can be reflected in pressure transient testing. The biggest challenge lies in delineating the pre-existing natural fracture distribution pattern, density, azimuth, and connectivity. Using the advanced finite element method, this paper builds a finely characterized near-wellbore model to numerically simulate the pressure transient testing process in naturally fractured reservoirs and further evaluates fracture-related effects to obtain a more accurate solution. First, the numerical program is benchmarked by the analytical solutions and numerical results of Eclipse. Next, different fracture models with single fractures or fracture networks are set up to investigate the effects of fracture parameters numerically (e.g., fracture location, fracture dip angle, fracture spacing, the ratio of fracture permeability to matrix permeability, fracture network orientation, horizontal fracture distribution, etc.) on pressure transient behaviors in naturally fractured reservoirs. Velocity and pressure profiles are presented to visualize and analyze their effects, and new features in the flow regimes of the derivative plots of the bottom-hole pressure are identified and discussed. Finally, based on geological and geophysical data, including image logs, core descriptions, wireline logs, and seismic and well test data, a practical fractured model of the Dalwogan 2 well in the Surat basin is built, analyzed, and compared with homogenous and measured data. The results show significance in characterizing the complex fracture networks in near-wellbore models of unconventional fractured reservoirs.

A Unique Volcanic Jatibarang Reservoir: Facies Characterization and Fracture Calculation

Jatibarang structure, situated in Jatibarang low, one of the prolific sub-basin in the northwest Java basin, belongs to PT. Pertamina EP working area. One hundred seventy wells have been drilled, from which there were 56 production wells. Forty production wells were sunk on a volcanic reservoir. Since 1970, volcanic Jatibarang has faced disputed facies concepts, porosities heterogeneity, and permeability system. A fractured reservoir model was proposed. It was due to unique high-performance hydrocarbon in the early years, and then steeply depleted in the early next 3 years, and flat over 20 years. A unique petrophysical method was developed with various explosives and effusive facies. This study proposes a new facies determination concept related to unavailable default petrophysical plots usually used in the clastic-carbonate reservoir. The new concept of formation evaluation attempts to distinguish the fractured vitric tuff reservoir and non-reservoir zone, which is both effusive lava and explosive product. Reservoirs differed from common clastic-carbonate, typically high gamma-ray reservoir due to potassium feldspar composition. The fracture existence is reflected by a sonic overrunning density log aligned with a deep resistivity pattern. The width of the fracture apertures was measured, and spacing intensities were calculated. Finally, fracture permeability was estimated comprehensively to describe reservoir performance. Property models built with only sonic and triple combo have been debatable; however, advanced logging of JTB-211 has proven this accuracy method.

Study on Permeability Stress-Sensitivity in Seepage-Geomechanical Coupling of Fractured Deep Tight Sandstone Gas Reservoirs

Accurately predicting the characteristics and influencing factors of permeability stress-sensitivity contributes to improving gas production in gas reservoirs. In this paper, the effects of effective stress on the permeability of fractured deep tight sandstone reservoirs were studied by laboratory tests. With the experimental results, a coupled seepage-geomechanical model for fractured deep tight sandstone gas reservoirs was constructed. The influences of pore pressure and geo-stress on permeability characteristics and gas production were studied by numerical simulation. The results indicate: (1) When the effective stress increases from 0 to 65 MPa, the permeability of the natural sample with fractures decreases by 81.28%, and the permeability of the intact core sample decreases by 54.67%. (2) When the pore pressure decreases from 120 to 85 MPa, the three-dimensional effective stress increases. The largest increase of the effective stress was along the vertical direction, which increased by 11~19 MPa. In addition, the permeability of the fractured zone and the intact rock along the vertical direction decreased by about 40% and 16%, respectively. (3) The mean square error between the historical gas production results and the results by simulation was 2.22 when considering the permeability stress-sensitivity, and 4.01 without considering the permeability stress-sensitivity. The proposed coupled seepage-geomechanical model with permeability stress-sensitivity proved to be more accurate in historical gas production comparison and prediction. This study provides a reliable optimization scheme for the development of fractured deep tight sandstone gas reservoirs.

Granitic Basement Fracture Analogue by Using Integrated Digital Outcrop Model and Fieldwork, at Muaro Silokek, West Sumatra

The study aims to determine fracture characteristics such as orientation, fracture attributes, fracture density distribution, and mineral composition of quartz and feldspar. The study used photogrammetry data to know the distribution and geometry of macro-scale fracture, linear scanline and windows scan data to understand the characteristics of mesoscale fracture attribute, and thin section rocks data from oriented samples to determine petrographic analysis and micro-scale fracture. After analyzing each of these data, analog basement fractured reservoir modeling could be built from integrating the data and modeling parameters based on available fieldwork data. The fault in the research area is represented as a Riedel shear with the orientation direction of NNW-SSE, NE-SW, and ENE-WSW. The fracture density is influenced by its position on the fault and increases in the fault damage zone. The granite type in the study area was divided into three types, namely alkali feldspar granite, syeno granite, and monzogranite. Each granite type has a different response to fractures and shows that the fracture density will increase with the greater quartz and k-feldspar in the fault damage zone. Fracture permeability values are strongly influenced by the geometry of fracture position, fracture aperture, and fracture length. This study produced a new perspective for fractured basement reservoirs, especially for granitic rocks, generally the primary target for basement fracture reservoirs along Sumatra.

Machine-learning-based well production prediction under geological and hydraulic fracture parameters uncertainty for unconventional shale gas reservoirs

Shale gas production prediction under history-matching-based geomodel is crucial to achieve reliable assessment and economic management of unconventional shale resources, however, conventional history matching is generally performed through repeatedly running high-fidelity reservoir simulations and therefore presents intensive computation-cost in practical applications. Without the need of history matching step, this work presents an efficient and robust post-history production forecasting framework using a latent-space learning-based direct forecast approach, e.g., referred to as LS-LDFA. A novel dimensionality reduction method, e.g., convolutional autoencoder, is employed to regularize the multi-well time-series data by low-order representation within a latent space. Once the machine-learning proxy is trained offline, the online post-history production forecast can be efficiently achieved by input history data. This paper presents some comparative studies between LS-LDFA and model-based history matching. This approach is tested on two examples with an increasing complexity, e.g., a multi-fractured horizontal well and a naturally fractured reservoir model with multi-well-pad-production based on synthetic shale formation. The results confirm that the method achieves high robustness and computational efficiency simultaneously in comparison with the conventional history matching. The application of learning-based direct forecast approach can effectively fuse information from history data and thus support reliable decision-making and risk assessment.

Scale discrepancy paradox between observation and modelling in fractured reservoir models in oil and gas industry

AbstractThe appraisal and development of fractured reservoirs are challenging tasks because of the combined variations in reservoir quality and natural fracture distribution. Fracture models are built routinely to support both appraisal and development decisions for such reservoirs. One of the key objectives of these models is to generate three-dimensional (3D) fracture properties for dynamic flow simulations. In this paper, we illustrate the discrepancy between the scale of observation required to build a thorough geological understanding of the subsurface and the simplification imposed by modelling. We use a case study carried out in the context of an exploration campaign of a Cretaceous carbonate reservoir in Egypt. After describing the regional geological setting of the area, we share a series of detailed observations on open-hole logs, cores, thin-sections and borehole images. These observations are focused on reservoir architecture, fracture typology and fracture connectivity. Observations are then integrated with the regional geological context to build a conceptual fracture model and to characterize the uncertainty affecting the essential parameters of this model. The conceptual model, combined with 3D seismic data, is used to define a fracture modelling strategy. This strategy includes a drastic simplification of the conceptual model to generate 3D discrete fracture network scenarios that are calibrated using pressure communication data from the exploration wells. Another extreme simplification is then necessary to populate 3D simulation grids. In the case study presented, the key tuning parameters to obtain a dynamic match are the grid cell orientation and the width of the modelled fault damage zone.

Causes of a premature thermal breakthrough of a hydrothermal project in Germany

Sustainable heat extraction is of utmost importance for the economic life of geothermal production systems. Especially in hydrothermal sedimentary basins, a temperature decrease at the production well prompts a financial loss. A premature thermal breakthrough occurred in one of the geothermal projects in the Greater Munich Area, a well-known region for deep, low enthalpy geothermal development in the Upper Jurassic carbonate reservoir (syn. Malm) beneath the North Alpine Foreland Basin. Accordingly, questions are raised regarding the geologic controls on the reservoir´s permeability, the occurring type of heat and mass transport mechanism, and the fitting reservoir model type. 3D seismic data interpretation delineates seismic scale structures potentially influencing the reservoir permeability. Geophysical borehole data characterize sub-seismic scale elements (fractures, karst, and lithofacies), where we correlate them with the inflow zones and the interpreted seismic scale structures. The integration of both scales delineates the reservoir heterogeneity controlled by a lateral change in the carbonate lithofacies overprinted by faults and fractures. A NNW-SSE oriented seismic scale structure matches the orientation of hydraulically active sub-seismic scale fractures, where they are aligned with the maximum horizontal stress orientation. This structure induces additional anisotropic permeability, providing a preferential hydraulic pathway between the wells of the project. This study recommends considering fractured reservoir models to simulate the mass and heat flow in the highly heterogeneous Malm carbonates instead of composite reservoir models of equivalent hydraulic properties. Finally, we present a hydrogeological model describing the reservoir's structural and matrix permeability distribution to act as a basic concept for future thermal-hydraulic numerical modeling. The applied methods in this study are applicable in similar geothermal systems with adequate seismic and geophysical borehole data for future geothermal reservoir characterization, modeling, and management.

Surrogate-assisted hydraulic fracture optimization workflow with applications for shale gas reservoir development: a comparative study of machine learning models

Unconventional reservoirs have become the main alternative for increasing oil and gas reserves around the world. Owing to their ultralow permeability properties and special pore structure, hydraulic fracturing technology is necessary to realize the efficient development and economic management of unconventional resources. To maximize the production capacity of wells, several fracture parameters, including fracture number, length, width, conductivity, and spacing, need to be optimized effectively. The optimization of hydraulic fracture parameters in shale gas reservoirs generally demands intensive computations owing to the necessity of numerous physicalmodel simulations. This study proposes a machine learning (ML)–assisted global optimization framework to rapidly obtain optimal fracture parameters. We employed three supervised ML models, including the radialbasis function, K-nearest neighbor, and multilayer perceptron, to emulate the relationship between fracture parameters and shale gas productivity for multistage fractured horizontal wells. Firstly, several forward shale gas simulations with embedded discrete fracture models generate training samples. Then, the samples are divided into training and testing samples to train these ML models and optimize network hyper parameters, respectively. Finally, the trained ML models are combined with an intelligent differential evolution algorithm to optimize the fracture parameters. This novel method has been applied to a naturally fractured reservoir model based on the real-field Barnett shale formation. The obtained results are compared with those of conventional optimizations with high-fidelity models. The results confirm the superiority of the proposed method owing to its very low computational cost. The use of ML modeling technology and an intelligent optimization algorithm could greatly contribute to simulation optimization and design, prompting progress in the intelligent development of unconventional oil and gas reservoirs in China.