The impacts of microcosmic flow in nanoscale shale matrix pores on the gas production of a hydraulically fractured shale-gas well

Summary One of the most-significant practical problems with the optimization of shale-gas-stimulation design is estimating post-fracture production rate, production decline, and ultimate recovery. Without a realistic prediction of the production-decline trend resulting from a given completion and given reservoir properties, it is impossible to evaluate the economic viability of producing natural gas from shale plays. Traditionally, decline-curve analysis (DCA) is commonly used to predict gas production and its decline trend to determine the estimated ultimate recovery (EUR), but its analysis cannot be used to analyze which factors influence the production-decline trend because of a lack of the underlying support of physics, which makes it difficult to guide completion designs or optimize field development. This study presents a unified shale-gas-reservoir model, which incorporates real-gas transport, nanoflow mechanisms, and geomechanics into a fractured-shale system. This model is used to predict shale-gas production under different reservoir scenarios and investigate which factors control its decline trend. The results and analysis presented in the article provide us with a better understanding of gas production and decline mechanisms in a shale-gas well with certain conditions of the reservoir characteristics. More-in-depth knowledge regarding the effects of factors controlling the behavior of the gas production can help us develop more-reliable models to forecast shale-gas-decline trend and ultimate recovery. This article also reveals that some commonly held beliefs may sound reasonable to infer the production-decline trend, but may not be true in a coupled reservoir system in reality.

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Numerical Analysis of Transient Pressure Behaviors with Shale Gas MFHWs Interference

Energies ◽

10.3390/en12020262 ◽

2019 ◽

Vol 12 (2) ◽

pp. 262 ◽

Cited By ~ 4

Author(s):

Dapeng Gao ◽

Yuewu Liu ◽

Daigang Wang ◽

Guofeng Han

Keyword(s):

Shale Gas ◽

Large Scale ◽

Horizontal Well ◽

Gas Production ◽

Pressure Recovery ◽

Hydraulic Fractures ◽

Transient Pressure ◽

Gas Well ◽

Well Pattern ◽

The Impact

After the large-scale horizontal well pattern development in shale gas fields, the problem of fast pressure drop and gas well abandonment caused by well interference becomes more serious. It is urgent to understand the downhole transient pressure and flow characteristics of multi-stage fracturing horizontal well (MFHW) with interference. Therefore, the reservoir around the MFHW is divided into three regions: fracturing fracture, Stimulated reservoir volume (SRV), and unmodified matrix. Then, multi-region coupled flow model is established according to reservoir physical property and flow mechanism of each part. The model is numerically solved using the perpendicular bisection (PEBI) grids and the finite volume method. The accuracy of the model is verified by analyzing the measured pressure recovery data of one practical shale gas well and fitting the monitoring data of the later production pressure. Finally, this model is used to analyze the effects of factors, such as hydraulic fractures’ connectivity, well distance, the number of neighboring wells and well pattern arrangement, on the transient pressure and seepage characteristics of the well. The study shows that the pressure recovery double logarithmic curves fall in later part when the well is disturbed by a neighboring production well. The earlier and more severe the interference, the sooner the curve falls off and the larger the amplitude shows. If the well distance is closer, and if there are more neighboring wells and interconnected corresponding fracturing segments, the more severe interference appears among the wells. Moreover, the well interference may still exist even without interlinked fractures or SRV. Especially, severe interference will affect production when the hydraulic fractures are connected directly, and the interference is weaker when only SRV induced fracture network combined between wells, which is beneficial to production sometimes. When severe well interference occurs, periodic well shut-in is needed to help restore the reservoir pressure and output capacity. In the meanwhile, the daily output should be controlled reasonably to prolong the stable production time. This research will help to understand the impact of well interference to gas production, and to optimize the well spacing and achieve satisfied performance.

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The prediction of shale gas well production rate based on grey system theory dynamic model GM(1, N)

Journal of Petroleum Exploration and Production Technology ◽

10.1007/s13202-020-00954-w ◽

2020 ◽

Vol 10 (8) ◽

pp. 3601-3607

Author(s):

Xiaohui Luo ◽

Xiaoqing Yan ◽

Yusong Chen ◽

Ming Yue ◽

Jingwei Li

Keyword(s):

Shale Gas ◽

Prediction Accuracy ◽

Original Data ◽

Gas Production ◽

Grey System Theory ◽

Data Series ◽

Physical Parameters ◽

Prediction Errors ◽

Grey System ◽

Gas Well

Abstract The prediction of production volumes from shale gas wells is important in reservoir development. The physical parameters of a reservoir are uncertain and complex, and therefore, it is very difficult to predict the production capability of a shale gas well. An improved GM(1, N) model for shale gas well productivity prediction, focused upon the causes of prediction errors from the existing traditional GM(1, N) method, was established. By processing a data series related to the predicted data, the improved GM(1, N) model takes into account the fluctuations of the original production data, reflects the trend of the original data under the influence of relevant factors, and hence predicts more accurately the fluctuation amplitude and direction of the original data. Additionally, the proposed method has higher accuracy than the conventional GM(1, N), GM(1, 1), and MEP models. The prediction accuracy increases gradually and the relative error decreases gradually from bottom data (casing pressure at well start-up, etc.) to top data (shale gas production). Accordingly, a step-by-step prediction method could be effective in improving prediction accuracy and reflects the typical fluctuation characteristics of shale gas production.

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Key Factors in Shale Gas Modeling and Simulation

Archives of Mining Sciences ◽

10.2478/amsc-2014-0068 ◽

2014 ◽

Vol 59 (4) ◽

pp. 987-1004 ◽

Cited By ~ 2

Author(s):

Łukasz Klimkowski ◽

Stanisław Nagy

Keyword(s):

Shale Gas ◽

Gas Production ◽

Production Performance ◽

Hydraulic Fractures ◽

Well Performance ◽

Key Factors ◽

Gas Well ◽

Well Production ◽

Multi Stage ◽

The Impact

Abstract Multi-stage hydraulic fracturing is the method for unlocking shale gas resources and maximizing horizontal well performance. Modeling the effects of stimulation and fluid flow in a medium with extremely low permeability is significantly different from modeling conventional deposits. Due to the complexity of the subject, a significant number of parameters can affect the production performance. For a better understanding of the specifics of unconventional resources it is necessary to determine the effect of various parameters on the gas production process and identification of parameters of major importance. As a result, it may help in designing more effective way to provide gas resources from shale rocks. Within the framework of this study a sensitivity analysis of the numerical model of shale gas reservoir, built based on the latest solutions used in industrial reservoir simulators, was performed. The impact of different reservoir and hydraulic fractures parameters on a horizontal shale gas well production performance was assessed and key factors were determined.

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Status and Influence of Shale Gas Well Integrity Failure

Materials Science Forum ◽

10.4028/www.scientific.net/msf.944.892 ◽

2019 ◽

Vol 944 ◽

pp. 892-897

Author(s):

Wen Bao Zhai ◽

Jun Li ◽

Yan Xi ◽

Gong Hui Liu ◽

Ying Сao Zhou

Keyword(s):

Failure Mechanism ◽

Shale Gas ◽

Structural Integrity ◽

Oil And Gas ◽

Gas Production ◽

Control Methods ◽

Gas Well ◽

Seal Integrity ◽

Well Integrity ◽

At Home

The well integrity issues in oil and gas wells have a long history, especially in the shale gas development, which has a direct impact on improving single well production of shale gas horizontal wells. Reviewing the domestic and foreign literature researches, the development status of major shale gas blocks at home and abroad were introduced. Well integrity failure characteristics of major shale gas blocks at home and abroad were counted and analyzed in detail. Finally, considering the shale gas development blocks in China as an example, the structural integrity (casing deformation) and seal integrity (Sustained Casing/Annulus pressure, SCP/SAP) were analyzed by clarifying the failure mechanism that well integrity issues affected shale gas production and that shale gas well integrity issues in China are a new problem was thought. The failure mechanism of shale gas well integrity needs to be further clarified, and a complete set of failure prediction and control methods has not yet been formed. Therefore, based on the concept of shale gas geology-engineering integration, taking into account the actual conditions of shale gas development blocks, it is proposed to scientifically and reasonably study shale gas well integrity failure mechanisms and their control methods, which has a reference and guidance to improve shale gas development.

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Sand Production of the Shale Gas Well in Different Production Periods: Structure and Component

Energies ◽

10.3390/en14175588 ◽

2021 ◽

Vol 14 (17) ◽

pp. 5588

Author(s):

Xiangchen Li ◽

Lin Yi ◽

Zhang Fan

Keyword(s):

Shale Gas ◽

Gas Production ◽

Size Analysis ◽

Production Test ◽

Sand Production ◽

Material Source ◽

Gas Well ◽

Sand Surface ◽

Large Size ◽

Sand Size

Complex geology and fracturing operations have led to frequent sand production problem in the shale gas well. Sand production brings huge engineering risks and seriously affects the normal production of the shale gas well. In order to study the property and source of the yielded sand, sand samples in three production periods of flowback, production test and gas production are collected from Sichuan Basin of China. Combining the methods of particle size analysis, microscope observation, scanning electron microscope, CT scanning, infrared spectroscopy and energy dispersive spectrum analysis, the multi-scale structure and composition characteristics of the yielded sand from different production periods were investigated. Results show that the sand size is the largest in the production test period and the smallest in the gas production period. The large-size sand is blocky in the flowback period, while it is flaky in the period of production test and gas production. The roundness of sand becomes worse as the sand size decreasing. Sand composition has the characteristics of fracturing proppant and shale mineral. Cementing material between large-size sands has the network structure and the higher content of aluminum and iron. Organic chemicals are found to be adhered to the sand surface in all three periods. Both shale fracture and proppant failure can generate particles that provide the material source for sand production. This research provides the source of the yielded sand and a theoretical guidance for the sand production mechanism.

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Economic benefit of shale gas exploitation based on back propagation neural network

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-189279 ◽

2020 ◽

Vol 39 (6) ◽

pp. 8823-8830

Author(s):

Jiafeng Li ◽

Hui Hu ◽

Xiang Li ◽

Qian Jin ◽

Tianhao Huang

Keyword(s):

Neural Network ◽

Shale Gas ◽

Bp Neural Network ◽

Large Scale ◽

Linear Prediction ◽

Back Propagation ◽

Back Propagation Neural Network ◽

Economic Benefits ◽

Gas Well ◽

Well Production

Under the influence of COVID-19, the economic benefits of shale gas development are greatly affected. With the large-scale development and utilization of shale gas in China, it is increasingly important to assess the economic impact of shale gas development. Therefore, this paper proposes a method for predicting the production of shale gas reservoirs, and uses back propagation (BP) neural network to nonlinearly fit reservoir reconstruction data to obtain shale gas well production forecasting models. Experiments show that compared with the traditional BP neural network, the proposed method can effectively improve the accuracy and stability of the prediction. There is a nonlinear correlation between reservoir reconstruction data and gas well production, which does not apply to traditional linear prediction methods

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