Fractured Horizontal Wells Research Articles

End of tubing placement optimization for multi-stage fractured horizontal wells by transient multiphase flow simulation

The exploitation of shale gas offers an effective pathway towards mitigating greenhouse gas emissions and promoting a clean and low-carbon energy system. Nonetheless, liquid loading has been commonly observed in the middle and late production stage, leading to sharp decline of shale gas production. How to improve unloading performance is challenging due to limited liquid-loading capacity. The strategic and timely installation of oil tubing serves as an effective means to mitigate wellbore fluid accumulation in the gas field. Thus, this work tries to improve gas recovery factor by optimizing the End of Tubing (EOT) location and the timing of tubing installation in shale gas wells through transient multiphase flow simulation. The transient simulation approach is adopted owing to its capability to accurately characterize the transient unloading process in gas wells and its closer approximation to field operation conditions compared to steady-state simulation methods. The casing production model and tubing production model have been developed to accurately simulate the flow behavior of fracturing fluid in the casing and tubing production, respectively. The annular flow and the coupling of fluid flow between reservoir and wellbore are the primary focuses of the two models aimed at analyzing fluid flow behavior and the total pressure drop (Δptotal). The casing production model is used to optimize the timing of tubing installation by simulating the liquid loading process of gas well including Δptotal and liquid inventory of wellbore. The optimal time of tubing placement is identified as the point when fluid starts to accumulate in the wellbore, as confirmed through the quantifiable analyses of Δptotal and liquid inventory. The tubing production model is further utilized to optimize the EOT location and tubing diameter considering variations in annular flow and the challenges associated with tubing installation. The placement of tubing in up-dip wells is recommended at Point A, which is determined by considering the influence of fluid gravity as a resistive force. Conversely, for down-dip wells, it is advisable to position the tubing between 1/3 of AB and 1/2 of AB as fluid gravity serves as a driving force in these scenarios. This work offers guidance for the optimum EOT location in shale gas reservoirs experiencing severe liquid loading. Consequently, it is essential to establish guidelines for determining the optimal EOT location across various horizontal well configurations and flow conditions.

Pressure Transient Analysis for Fractured Shale Gas Wells Using Trilinear Flow Model

Shale gas, a low-permeability, unconventional resource, requires horizontal drilling and multi-stage fracturing for commercial production. This study develops a trilinear flow model for fractured horizontal wells in shale gas formations, incorporating key mechanisms such as adsorption, desorption, diffusion, wellbore storage, and skin effects. The model delineates seven distinct flow regimes, providing insights into gas migration processes and the factors controlling production. Sensitivity analyses reveal that desorption plays a critical role under low-pressure and low-production conditions, significantly enhancing gas transfer rates from the matrix to the fracture network and contributing to overall production. Monte Carlo simulations further highlight the variability in pressure responses under different input conditions, offering a comprehensive understanding of the model’s behavior in complex reservoir environments. These findings advance the characterization of shale gas flow dynamics and inform the optimization of production strategies.

Application of Machine Learning to Predict the Capacity of Fractured Horizontal Wells in Shale Reservoirs

Shale oil wells typically have numerous volume fracturing segments in their horizontal sections, resulting in significant variability in productivity across these segments. Conventional productivity prediction and fracturing effect evaluation methods are challenging to apply effectively. Establishing a stable and efficient intelligent productivity prediction method using machine learning is a promising approach for the effective development of shale oil reservoirs. This study is based on geological data, fracturing records, and a production database of 91 production wells in a shale oil reservoir in a specific area. Fourteen key parameters affecting productivity were selected from geological and engineering perspectives, and the recursive feature elimination method based on support vector machines identified five optimal main controlling factors. Three machine learning methods—decision tree, random forest, and gradient boosting decision tree (GBDT)—were used to model productivity prediction, with root mean square error (RMSE) employed to evaluate model performance. The study results indicate that formation coefficient, cluster spacing, treatment volume, sand volume, and fracturing segment length are the main controlling factors influencing productivity in fractured horizontal wells. Among the models, the random forest algorithm with bootstrap sampling produced the most stable prediction results, achieving a prediction accuracy of 94% and an RMSE of 0.934 on the test set, outperforming the decision tree and GBDT models in terms of minimum RMSE on the test set.

Production Simulation of Stimulated Reservoir Volume in Gas Hydrate Formation with Three-Dimensional Embedded Discrete Fracture Model

Natural gas hydrates (NGHs) in the Shenhu area of the South China Sea are deposited in low-permeability clayey silt sediments. As a renewable energy source with such a low carbon emission, the exploitation and recovery rate of NGH make it difficult to meet industrial requirements using existing development strategies. Research into an economically rewarding method of gas hydrate development is important for sustainable energy development. Hydraulic fracturing is an effective stimulation technique to improve the fluid conductivity. In this paper, an efficient three-dimensional embedded discrete fracture model is developed to investigate the production simulation of hydraulically fractured gas hydrate reservoirs considering the stimulated reservoir volume (SRV). The proposed model is applied to a hydraulically fractured production evaluation of vertical wells, horizontal wells, and complex structural wells. To verify the feasibility of the method, three test cases are established for different well types as well as different fractures. The effects of fracture position, fracture conductivity, fracture half-length, and stimulated reservoir volume size on gas production are presented. The results show that the production enhancement in multi-stage fractured horizontal wells is obvious compared to that of vertical wells, while spiral multilateral wells are less sensitive to fractures due to the distribution of wellbore branches and perforation points. Appropriate stimulated reservoir volume size can obtain high gas production and production efficiency.

An integrated workflow of history matching and production prediction for fractured horizontal wells

This paper presents a novel method for history matching and production prediction for fractured horizontal wells by combining the data space inversion method (DSI) with the embedded discrete fracture model (EDFM), referred to as DSI-EDFM. In this approach, several initial numerical models with varying reservoir geological and fracture geometry parameters, but identical production schedules, are generated through random sampling and then run using the EDFM. The DSI method is subsequently employed to process the production data, creating a proxy model that matches actual historical data and predicts production performance by solving a quadratic optimization problem. A key improvement over the original DSI method is introduced, providing and proving the conditions under which the optimization problem derived from DSI is a positive definite quadratic optimization problem. With these conditions, the optimal solution can be directly obtained using the Newton method without any iterations. Furthermore, it is identified that overfitting issues frequently arise when using the Newton method for DSI. However, the simultaneous perturbation stochastic approximation algorithm effectively mitigates this problem, allowing the proposed DSI-EDFM to handle real reservoirs and uncertainty parameters efficiently. Three numerical examples are implemented to validate the method, including depleting development, water flooding operations, and the flush stage of fractured horizontal wells. The results demonstrate that the proposed DSI-EDFM achieves high accuracy in conducting history matching and performance prediction for fractured horizontal wells, even under complex flow model conditions and with a limited number of initial models. Additionally, the accuracy improves as the number of initial models increases.

Predicting the productivity of fractured horizontal wells using few-shot learning

Predicting the productivity of multistage fractured horizontal wells plays an important role in exploiting unconventional resources. In recent years, machine learning (ML) models have emerged as a new approach for such studies. However, the scarcity of sufficient real data for model training often leads to imprecise predictions, even though the models trained with real data better characterize geological and engineering features. To tackle this issue, we propose an ML model that can obtain reliable results even with a small amount of data samples. Our model integrates the synthetic minority oversampling technique (SMOTE) to expand the data volume, the support vector machine (SVM) for model training, and the particle swarm optimization (PSO) algorithm for optimizing hyperparameters. To enhance the model performance, we conduct feature fusion and dimensionality reduction. Additionally, we examine the influences of different sample sizes and ML models for training. The proposed model demonstrates higher prediction accuracy and generalization ability, achieving a predicted R2 value of up to 0.9 for the test set, compared to the traditional ML techniques with an R2 of 0.13. This model accurately predicts the production of fractured horizontal wells even with limited samples, supplying an efficient tool for optimizing the production of unconventional resources. Importantly, the model holds the potential applicability to address similar challenges in other fields constrained by scarce data samples.

Well test inversion method for fractured horizontal wells based on deep neural network

Well-test interpretation is an important means to obtain reservoir parameters. However, the traditional well test interpretation method of fractured horizontal wells is limited due to the computational efficiency of the well test model. This paper proposes an automatic interpretation method for well-test curves based on neural networks. Considering the basic parameters of the reservoir, the dimensional pressure, pressure derivative, and time data are used as samples to train the network. The well test data are processed and input into the trained optimal network to automatically identify well test parameters such as reservoir permeability. Mini-batch gradient descent with a batch size of 32 was used to train the network. The results showed that the network training achieved a lower loss function value and the best performance. Adaptive learning rate decay and increased samples were adopted to improve the parameter inversion accuracy. In addition, the two-dimensional convolutional neural network was compared with the fully connected neural network. We validate the results that the two-dimensional convolutional neural network had better parameter inversion accuracy and noise resistance than the fully connected neural network. Finally, two cases were used to further verify the parameter inversion model.

Research and application of migration and plugging mechanism of temporary plugging balls in multicluster fracturing of horizontal wells

Plugging and diverting stimulation technology using temporary plugging balls (PDSTB) in horizontal wells is one of the effective measures to enhance production in heterogeneous carbonate reservoirs. However, the migration and plugging mechanism of temporary plugging balls in horizontal wells remain unclear, leading to suboptimal field application. Based on the Lagrangian method, the migration and plugging models of temporary plugging balls were established. The study investigated the migration and plugging mechanism of temporary plugging balls. It analyzed the effects of parameters such as displacement on the plugging efficiency. The results show that the flow field in the perforation section is significantly affected by the displacement. Temporary plugging balls show three states of plugging: one ball plugging one shot-hole, multiple balls plugging one shot-hole, and balls remaining in the wellbore. The plugging efficiency initially increases, and then, decreases with the increase in displacement and the ball diameter. The plugging efficiency initially increases, and then, stabilizes with the increase in the viscosity of the carrying fluid and the usage ratio of balls. Plugging efficiency decreases with increasing density of balls. The greater the pressure difference at the outlet of the perforation section, the higher the plugging efficiency in the advantageous inlet section. Based on these results, the field construction of Well M was guided. The gas production was 142.66 × 104 m3/d after stimulation, and the production increase was significant. This study provides a theoretical basis for optimizing and designing the parameters of PDSTB in carbonate long horizontal wells.

Study on multi-cluster fracture interlaced competition propagation model of hydraulic fracturing in heterogeneous reservoir

The heterogeneity of the reservoir plays a crucial role in influencing the propagation of multi-cluster hydraulic fractures in horizontal wells. To explore this impact, a seepage-stress-damage coupled model was developed in this study for analyzing the competitive propagation of multi-cluster fractures utilizing the finite-discrete element method. Utilizing the model, a random assignment program has been developed to establish the coupling distribution of mechanical parameters between matrix elements and discrete elements for characterizing the reservoir heterogeneity. Simultaneously, a wellbore flow model describing the pressure drop of fracturing fluid flow is developed by introducing pipe flow element and fluid connection element, enabling the realization of dynamic flow distribution. Based on the developed model, an investigation is conducted into the impact of pumping rates, fracturing fluid viscosity, and perforation parameters on the fracture propagation of multi-cluster fracturing. The study findings suggest that as reservoir heterogeneity increases, the distribution of rock strength becomes more uneven, resulting in a more complex morphology of fracture propagation. Higher pumping rates lead to elevated pressure within fractures, thereby facilitating the uniform propagation of multi-cluster fractures, particularly in reservoir characterized by medium to high heterogeneity. Increasing the viscosity of fracturing fluid can diminish the tortuosity of multi-cluster fracture propagation, albeit with a somewhat limited enhancement in uniformity. As reservoir heterogeneity intensifies, the interference between fractures escalates, necessitating a reduced number of perforations to heighten perforation friction and enhance the balanced propagation of multi-cluster fractures. This research offers theoretical guidance and a scientific foundation for the design of schemes and optimization of parameters in staged multi-cluster fracturing technology for horizontal wells in heterogeneous reservoirs.

Analysis of the Impact of Clusters on Productivity of Multi-Fracturing Horizontal Well in Shale Gas

Shale gas reservoirs with nanoporous media have become one of the primary resources for natural gas development. The nanopore diameters of shale reservoirs range from 5 to 200 nm, with permeability ranging from 1 × 10−9 to 1 × 10−6 μm2. The natural gas production from shale gas reservoirs is low, necessitating the use of multi-stage hydraulic fracturing in horizontal wells. Segmented multi-cluster perforation fracturing is an effective method for shale gas extraction in these wells. The number of clusters significantly impacts the productivity of horizontal wells. Therefore, it is essential to analyze the impact of cluster numbers on fracture productivity in shale gas reservoir development. In this study, the equivalent flow resistance method was applied to establish a productivity model for multi-stage hydraulic fracturing horizontal wells in shale gas reservoirs considering diffusion and slip. An approximate analytical solution was obtained, and the effects of cluster length, diffusion coefficient, and fracture network permeability on productivity were analyzed. The results show that gas production gradually increases with the increase in the number of clusters and cluster length. However, as the number of clusters increases, the interference between clusters leads to a decrease in the productivity of individual clusters. As the fracture permeability, fracture network permeability, and diffusion coefficient increase, shale gas production also gradually increases. The permeability of the fracture network has the greatest impact on productivity. These research results are beneficial for the design of clusters in horizontal well fracturing and are of great importance for the development and production of shale gas reservoirs.

Evolution mechanism of deviated well fiber-optic strain induced by single-fracture propagation during fracturing in horizontal wells

Considering the high construction cost of horizontal adjacent well monitoring and the lack of vertical adjacent well fiber optic for obtaining fracturing information, this paper proposes the use of deviated wells with fiber optics for monitoring purposes. To demonstrate the advantages of deviated well fiber optics and the feasibility of their deployment, this paper constructs a forward model based on the finite element coupled with cohesive element approach to simulate the strain induced by the propagation of a single hydraulic fracture in horizontal wells on deviated well fiber optics, and conducts a numerical simulation analysis of the strain induced by the propagation of a single hydraulic fracture on deviated well fiber optics. The results show that the strain evolution induced by single-fracture propagation in deviated well fiber optics can be divided into four stages: strain-enhancing, strain-converging, tensile strain-expanding, and linear strain-converging. The strain evolution characteristics of deviated well fiber optics are manifested as follows: a “heart-shaped” tensile strain convergence zone with a certain deviation appears in the middle, which subsequently converges into a tensile strain convergence band, with compressive strain convergence zones on both sides, and an expanding tensile strain convergence zone on the outer side of the compressive strain convergence band. The analysis finds that when the well inclination angle is greater than 45°, the strain response characteristics of deviated well fiber optics are mainly governed by the width expansion of the fracture, and when less than 45°, they are mainly governed by the height expansion of the fracture. Changes in the azimuth angle can cause a deviation of the “heart-shaped” tensile strain area and the compressive strain convergence zone in the fiber-optic strain waterfall plot, with larger deviations corresponding to smaller azimuth angles. The depth at which the deviated well fiber optics are deployed, reaching the depth of the horizontal section of the horizontal well, can reflect the upward expansion of the fracture height. The results of the analysis illustrate the advantages of deviated well fiber optics in obtaining both fracture width and height expansion information simultaneously and propose a method for selecting suitable deviated well fiber-optic construction parameters based on fracturing monitoring needs. This research can reduce the construction cost of deploying fiber optics in adjacent wells and has significant implications for guiding the layout of adjacent well fiber optics.

Sensitivity Analysis of Depth-Controlled Oriented Perforation in Horizontal Wells Based on the 3D Lattice Method

The main method used to exploit unconventional oil and gas reservoirs involves multi-cluster perforation combined with hydraulic fracturing in horizontal wells. However, as the use of this technology has expanded, challenges like reduced perforation efficiency and elevated fracture initiation pressure have surfaced. The depth-controlled oriented perforation technique helps achieve uniform fracture initiation, enhance efficiency, and lower initiation pressure. In this study, a hydraulic fracturing fluid–solid coupling model at the perforation scale was established using the 3D lattice method to compare the near-wellbore fracture morphologies of depth-controlled oriented perforation, spiral perforation, and oriented perforation. Additionally, this study analyzes the effects of injection rate, reservoir elastic modulus, and horizontal stress difference on the fracture morphology and initiation pressure of depth-controlled oriented perforation. This study clarifies the applicability of depth-controlled oriented perforation in different types of reservoirs for the first time. The results indicate that intermediate fractures between spiral and oriented perforations are hindered, while depth-controlled oriented perforation ensures uniform fracture initiation. In the injection rate range of 0.144 to 0.360 L/min, an increase in injection rate accelerates the rise of fluid pressure within the perforations, leading to an increase in fracture initiation pressure. Therefore, excessively high injection rates are unfavorable for fracture initiation. Through depth-controlled oriented perforation, long and singular fractures can be formed in reservoirs with significant horizontal stress differences and high elastic moduli.

Study on Temporary Plugging Agents and Process Simulation for Offshore Low-permeability Reservoirs Fracturing

Abstract Temporary plugging fracturing technology is an effective method for extending the range of segmented fracturing in horizontal wells and improving the utilization between fractures in low-permeability reservoirs. In this study, a controllable degradable temporary plugging agent was synthesized by graft copolymerization of PGA and PLA with a material ratio of 3:1, under the catalysis of stannous octoate at 150°C. This approach allows for controlled degradation of the temporary plugging materials by protecting PLA, which has good affinity to water, and adjusting the molecular weight of the product. It reduces the initial degradation rate while increasing the later degradation rate. To consider the heterogeneity of natural fractures and reservoir physical permeability in shallow sea reservoirs, a numerical model for temporary plugging and fracturing of horizontal wells was developed. The model investigates the influence of parameters such as displacement and cluster spacing on crack propagation, resulting in the formation of a simulation method suitable for temporary plugging fracturing of horizontal wells in heterogeneous reservoirs. The research findings indicate that crack length and width gradually increase with the increase of displacement. The maximum crack spread area is achieved at a displacement of 5~8m3/min. Temporary plugging can be implemented when the cluster spacing is ≤12m, allowing for the full expansion of cracks that have not effectively expanded. The largest crack spread area is observed at a crack spacing of 5~8m.

Feasibility of CO2 storage and enhanced gas recovery in depleted tight sandstone gas reservoirs within multi-stage fracturing horizontal wells

Injecting CO2 when the gas reservoir of tight sandstone is depleted can achieve the dual purposes of greenhouse gas storage and enhanced gas recovery (CS-EGR). To evaluate the feasibility of CO2 injection to enhance gas recovery and understand the production mechanism, a numerical simulation model of CS-EGR in multi-stage fracturing horizontal wells is established. The behavior of gas production and CO2 sequestration is then analyzed through numerical simulation, and the impact of fracture parameters on production performance is examined. Simulation results show that the production rate increases significantly and a large amount of CO2 is stored in the reservoir, proving the technical potential. However, hydraulic fractures accelerate CO2 breakthrough, resulting in lower gas recovery and lower CO2 storage than in gas reservoirs without fracturing. Increasing the length of hydraulic fractures can significantly increase CH4 production, but CO2 breakthrough will advance. Staggered and spaced perforation of hydraulic fractures in injection wells and production wells changes the fluid flow path, which can delay CO2 breakthrough and benefit production efficiency. The fracture network of massive hydraulic fracturing has a positive effect on the CS-EGR. As a result, CH4 production, gas recovery, and CO2 storage increase with the increase in stimulated reservoir volume.

Augmented Depletion Development Technology Assessed Across US Shale Plays

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 217792, “Assessment of Augmented Depletion Development Technology Across US Shale Plays,” by Ahmed Merzoug, SPE, Texas A&M University, and Vibhas J. Pandey, SPE, ConocoPhillips. The paper has not been peer reviewed. _ The concept of augmented depletion development (ADD) was introduced to the industry through a pilot project conducted in the Bakken play in the US. These wells are openhole wells drilled within the fractured network of a pad. They are not fracture stimulated deliberately but do produce and contribute to the overall production of the lease. In this study, numerical modeling is used to understand the potential performance of these wells in several plays across the US. The learnings from this study can be used as a benchmark for operators that are planning on implementing such wells in their field development programs. Theoretical Basis of Study The concept of ADD can be modeled using a similar approach to the analytical solutions developed for flow into a multistage fractured horizontal well. In these wells, several regimes can be identified, such as transient linear flow and boundary-dominated flow. In previous work in the literature that proposed a method for analyzing production data of linear flow of fractured gas wells, fractures were assumed to have infinite dimensionless conductivity. Those researchers proposed a solution for a constant bottomhole-pressure liquid flow that is described in the present complete paper by a series of equations. For the case used by the present authors, a well spacing of 300 ft is assumed, implying that the perpendicular distance from the wellbore to a corresponding boundary is 150 ft, which is half the spacing between the fractured well and the ADD well (assuming each well drains half the fracture length). To elaborate further for better understanding of production, a plot of product of cumulative dimensionless rate and formation permeability (as a proxy for cumulative rate) while assuming all other properties behave the same shows that, with higher permeability, the recovery potential not only increases but also appears to accelerate. This supports the concept that, during the time of production of ADD wells, it is preferable to have higher permeabilities that can support faster production in zones that the primary wells may not drain effectively. The results of the analytical equation are for only one fracture but can be readily extended to multifractured horizontal wells using superposition methods. Methodology This study uses physics-based numerical modeling to simulate the performance of ADD wells in different plays. The numerical code simulates wellbore flow, hydraulic fracturing, geomechanics, and reservoir flow, all in the same package. The fracture and reservoir mesh are independent. The flow between the matrix and the reservoir is calculated using the 1D submesh approximation to reduce the computation expenses with higher accuracy. The hydraulic fracturing propagation algorithm uses a tip-tracking algorithm to allow the use of larger grid size without compromising accuracy in layered formations. The fracture conductivity is calculated with stress changes. The conductivity profile changes from a propped fracture into an unpropped fracture. The unpropped fracture conductivity is an underlying assumption used in this study. The collision between fractures initiated from different wells also is an assumption in this study.

Dynamic Evolution Law of Production Stress Field in Fractured Tight Sandstone Horizontal Wells Considering Stress Sensitivity of Multiple Media

Inter-well frac-hit has become an important challenge in the development of unconventional oil and gas resources such as fractured tight sandstone. Due to the presence of hydraulic fracturing fractures, secondary induced fractures, natural fractures, and other seepage media in real formations, the acquisition of stress fields requires the coupling effect of seepage and stress. In this process, there is also stress sensitivity, which leads to unclear dynamic evolution laws of stress fields and increases the difficulty of the staged multi-cluster fracturing of horizontal wells. The use of a multi-stage stress-sensitive horizontal well production stress field prediction model is an effective means of analyzing the influence of natural fracture parameters, main fracture parameters, and multi-stage stress sensitivity coefficients on the stress field. This article considers multi-stage stress sensitivity and, based on fractured sandstone reservoir parameters, establishes a numerical model for the dynamic evolution of the production stress field in horizontal wells with matrix self-supporting fracture-supported fracture–seepage–stress coupling. The influence of various factors on the production stress field is analyzed. The results show that under constant pressure production, for low-permeability reservoirs, multi-stage stress sensitivity has a relatively low impact on reservoir stress, and the amplitude of principal stress change in the entire fracture length direction is only within the range of 0.27%, with no significant change in stress distribution; The parameters of the main fracture have a significant impact on the stress field, with a variation amplitude of within 2.85%. The ability of stress to diffuse from the fracture tip to the surrounding areas is stronger, and the stress concentration area spreads from an elliptical distribution to a semi-circular distribution. The random natural fracture parameters have a significant impact on pore pressure. As the density and angle of the fractures increase, the pore pressure changes within the range of 3.32%, and the diffusion area of pore pressure significantly increases, making it easy to communicate with the reservoir on both sides of the fractures.

An improved mathematical model of gas–water two-phase flows in fractured horizontal wells accounting for physical contact behaviors of fractures with total factor characteristics

In water-bearing gas reservoirs, water existence affects gas production performances due to two-phase flows occurring in matrix and fracture systems. Under the background of staged multi-cluster fractured horizontal wells, this work focuses on an improved gas–water two-phase flow model accounting for physical contact behaviors of fractures with total factor characteristics. Combining a point-convergence method with fractal theory and applying Laplace transform and Stehfest numerical inversion, analytical solutions of this proposed model are solved to validate against the field production data and numerical simulation results. Subsequently, the analytical nephograms of formation pressure and water saturation at different stages are given for the first time, throughout which formation pressure and water saturation distributions at different locations of the fractured reservoir embedded with segmented multi-cluster tree-shaped fracture networks are visually exhibited. The results demonstrate that draining area evolution is limited to each segment at early stage and mid-stage, whereas these multi-cluster segments are really integrated into the whole draining area at late stage. Thus, the moving boundary of fracture-controlled unit is also delineated based on water saturation nephograms and expands with continuous production from 65 to 180 m in the y axis direction, contributing to the effective fracturing area for a high productivity. Furthermore, the share of free gas and adsorbed gas are 83% and 17% at early stage, while free gas and adsorbed gas account for 57% and 43% of total gas at the late stage. Those findings contribute to high-efficient and sustainable development of unconventional gas resources.

A semi-analytical mathematical model of off-center multi-stage fractured horizontal well in circle bi-zonal gas reservoir

A semi-analytical mathematical model of off-center multi-stage fractured horizontal well in circle bi-zonal gas reservoir

Optimization of Jiyang depression block X shale condensate reservoir well spacing based on geology–engineering integration

Appropriate well spacing is crucial for the efficient development of shale reservoirs, as it is closely related to the degree of resource utilization. Well spacing design is influenced by both fracturing processes and geological characteristics. While increasing well density can enhance reservoir recovery, it may lead to higher investment costs and significant well interference issues. In this study, we adopted an integrated geological–engineering approach, combining fracture propagation simulation, EDFM (Embedded Discrete Fracture Modeling), and numerical simulation methods to comprehensively analyze well interference under different well spacings in shale condensate reservoirs. Development well spacing was optimized using the degree of resource utilization and well interference rate as key indicators. There are three main research findings: (1) The geological engineering integration approach allows for differentiated well spacing according to specific research areas. Combining this integrated approach with EDFM and leveraging quantitative evaluation, we have developed an efficient and precise methodology for well spacing optimization. (2) When well spacing is less than the length of hydraulic fractures, inter-well fractures exhibit an entangled pattern, reducing the effectiveness of fracturing treatments and causing severe well interference. As well spacing increases, interference between fractures from different wells diminishes, but unstimulated volumes gradually emerge, leading to a decrease in reservoir recovery. (3) Considering both well interference and resource utilization, a well spacing of 400 m is recommended in the study area. At this spacing, interference between hydraulic fractures from different wells is minimal. After 10 years of production, the estimated reservoir recovery is 39.16%, with a production rate of 25.58% and a well interference rate of 13.58%. These research outcomes provide valuable insights for optimizing the well spacing of hydraulic fractured horizontal wells in shale condensate reservoirs.

Dynamic prediction of fracture propagation in horizontal well hydraulic fracturing: A data-driven approach for geo-energy exploitation

Accurate and efficient prediction of hydraulic fracturing fracture propagation is of utmost importance for unconventional reservoir development. Traditional numerical simulation methods require specialized domain knowledge and technical expertise, and machine learning approach can be an alternative predictive tool for fracture propagation. Additionally, existing neural networks cannot be directly applied to hydraulic fracturing scenarios influenced by multiple coupled factors. Thus, this study presents an innovative approach, “AE-ATT-ConvLSTM”, that integrates an additional Convolutional Layer, Autoencoder, and an Attention Mechanism Feature Fusion Layer into the architecture of a Convolutional Long Short-Term Memory (ConvLSTM) sequential image prediction network. This approach aims to predict fracture propagations in different fracturing stages of horizontal wells. The proposed model is trained on a sample dataset consisting of 5000 instances of hydraulic fracturing in horizontal wells. The dataset includes crucial data such as fracture propagation images, wellbore perforation images, natural fracture images, pumping schedules, and reservoir properties. The model achieves remarkable results, with an MSE less than 15 × 10−5, a maximum SSIM of 0.93, and an average FMAE less than 48. The research findings demonstrate that this method significantly enhances prediction efficiency and provides new insights for predicting fracture morphology and optimizing fracturing design.