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Due to strong stress sensitivity resulted from unconventional tight formationsit is of practical interest to formulate a reasonable pressure drawdown plan to improve gas extraction recovery. The impact of water-shale interactions on the reservoir permeability was previously ignored in the managed pressure drawdown optimization. The controlled-pressure production dynamic analysis was mostly conducted using numerical simulation, lack of rigorous theoretical support. Hence in this paper, a theoretical production prediction model was proposed and verified with HIS RTA 2015by incorporating multiple pressure drawdown mechanisms and various non-linear gas flow process. The on-site production effects dominated by two different pressure drop methods was further compared, indicating that compared to depressurization production, the production reversion can occur in the controlled pressure production process and the EUR of single well can be increased by about 30% under the control of managed pressure drawdown approach. Finally, the pressure drawdown optimization strategy was carried out on the field test from the both production effect and economic benefits, which demonstrated that the best economic solution can generally be obtained in the early stage of production. The research results can be closely linked to the on-site production practice of shale gas wells, providing insights into designing optimized production strategy scheme. [ABSTRACT FROM AUTHOR]

The shale gas productivity model based on shale gas nonlinear seepage mechanism is an effective way to reasonably predict productivity. The incomplete gas nonlinear effects considered in the current production prediction models can lead to inaccurate production prediction. Based on the conventional five-zone compound flow model, comprehensive gas nonlinearities were considered in the improved compound linear flow model proposed in the paper and a semianalytical solution for productivity was obtained. The reliability of the productivity model was verified by the field data, and then, the 20-year production performance analysis of the gas well was studied. Ultimately, the key influencing factors of the fracture control stage and matrix control stage have been analyzed. Research indicated the following: (1) the EUR predicted by the productivity model is higher than the EUR that the comprehensive nonlinear effects are not considered, which demonstrated that the various nonlinear effects cannot be neglected during the production prediction to ensure the greater calculation accuracy; (2) during the early production stage of shale reservoir, the adsorbed gas is basically not recovered, and the cumulative adsorption contribution rate does not exceed 10%. The final adsorption gas contribution rate is 23.28%, and the annual adsorption rate can exceed 50% in the 20th year, showing that free gas and adsorbed gas are, respectively, important sources of the early stage of production and long-term stable production; (3) the widely ranged three-dimensional fracturing reformation of shale reservoirs and reasonable bottom hole pressure in the later matrix development process should be implemented to increase the effective early production of the reservoir and ensure the earlier gas production process of the matrix development. The findings of this study can help for better ensuring the prediction accuracy of the estimated ultimate recovery and understanding the main influencing factors of the dynamic performance of gas wells so as to provide a theoretical reference for production optimization and development plan formulation of the shale gas reservoirs. [ABSTRACT FROM AUTHOR]

The shale gas productivity model based on shale gas nonlinear seepage mechanism is an effective way to reasonably predict productivity. The incomplete gas nonlinear effects considered in the current production prediction models can lead to inaccurate production prediction. Based on the conventional five-zone compound flow model, comprehensive gas nonlinearities were considered in the improved compound linear flow model proposed in the paper and a semianalytical solution for productivity was obtained. The reliability of the productivity model was verified by the field data, and then, the 20-year production performance analysis of the gas well was studied. Ultimately, the key influencing factors of the fracture control stage and matrix control stage have been analyzed. Research indicated the following: (1) the EUR predicted by the productivity model is higher than the EUR that the comprehensive nonlinear effects are not considered, which demonstrated that the various nonlinear effects cannot be neglected during the production prediction to ensure the greater calculation accuracy; (2) during the early production stage of shale reservoir, the adsorbed gas is basically not recovered, and the cumulative adsorption contribution rate does not exceed 10%. The final adsorption gas contribution rate is 23.28%, and the annual adsorption rate can exceed 50% in the 20th year, showing that free gas and adsorbed gas are, respectively, important sources of the early stage of production and long-term stable production; (3) the widely ranged three-dimensional fracturing reformation of shale reservoirs and reasonable bottom hole pressure in the later matrix development process should be implemented to increase the effective early production of the reservoir and ensure the earlier gas production process of the matrix development. The findings of this study can help for better ensuring the prediction accuracy of the estimated ultimate recovery and understanding the main influencing factors of the dynamic performance of gas wells so as to provide a theoretical reference for production optimization and development plan formulation of the shale gas reservoirs. [ABSTRACT FROM AUTHOR]

Predicting the production behaviors of shale gas wells is of great importance for further developing future unconventional hydrocarbon strategies. An accurate prediction production, as well as reliable shale gas production models, are required to fully understand the shale gas exploitation budget. However, a major problem with classical analytic methods is the insufficient accuracy of the existing models, the time-consuming collection of historical production data, and the costly computational expense. To minimize this problem, a combination of the exponential smoothing method, autoregressive integrated moving average (ARIMA) model, and long short-term memory (LSTM) model was proposed to provide robust support for the production behaviors of shale gas. In this paper, we employed shale gas well production data to establish a database for model training and optimized the predicted model. Hereby, we sought to evaluate the production data predicted by conventional analytical methods, the exponential smoothing method, the ARIMA model, and the LSTM model. Shortly afterward, we objectively compared the predicted results obtained by the novel LSTM model and traditional analytical methods, such as Arps, stretched exponential decline (SEPD), and the Duong model. Herein, we compared the computational cost between the LSTM model and traditional numerical simulation. The combined interpretation of the proposed model demonstrates that the LSTM model achieved scientific accuracy and outstanding results in both short-term and long-term predictions, and realized production prediction of the adjacent well, with excellent agreement with the real shale gas production and a low error, making it an effective tool in forecasting shale gas production. This assay could be used as a potential approach for evaluating deep learning in the petroleum industry and for predicting the future production of unconventional hydrocarbons. [Display omitted] • A framework for shale gas production potential estimation was developed. • A deep-learning-based time series analysis model was built to predict the short-term and longterm shale gas production, based on thousands of in-situ production data samples from three shale gas wells. • Computational cost of the shale gas production prediction was significantly reduced with proposed long short-term memory model. • Objectively compare the advantage and drawback forecasting production among conventional analytical methods, exponential smoothing algorithm, ARIMA, and LSTM model. • The study shed lights on the few-shot learning applications in shale gas production prediction. [ABSTRACT FROM AUTHOR]

As an unconventional natural gas resource, shale gas is attracting increasing attention worldwide because of its potential to strengthen global energy security and reduce carbon emissions. The shale gas flow in nanopores is one of the main concerns affecting its development process. However, due to the strong nonlinearity and complexity of gas flow at the nanoscale, there is no satisfactory consensus on a physically sound flow mechanism scheme and its corresponding coupling method. Furthermore, although the integration method using specific functions has been proposed to facilitate the consideration of various pore sizes in shale matrix, the real shale experiments are rarely involved to realize this integration method with definitely determined parameters. In this study, the concept of "wall-associated diffusion" is firstly utilized to clarify the relationship among several flow mechanisms, and thereby a comprehensive flow mechanism scheme differing from common research is proposed, which physically considers both the division of mechanical mechanisms in nanopores and partition of flow space. Besides, the deficiencies in the mathematical models of viscous flow and several diffusion processes for flow description are illustrated. Using the molecular collision frequency expressions, a new coupling coefficient-based flow model in nanopores is derived to eliminate the aforementioned deficiencies by strengthening the correspondence between the flow models and Knudsen number (Kn), which is applicable in the full flow regime scope and avoids segment processing. Furthermore, based on the pore size distribution experiments of the real shale samples from a gas field, the fitting parameters needed for the macroscopic form of the above coupled model are obtained, so as to establish an integration method-based unified model for gas flow prediction in shale matrix. Results show that the prediction accuracy of the new model for the two tested shale samples is at least 2.2 times higher than several typical models and is also 1.9 and 7.5 times more accurate than the model without coupling coefficients, respectively. And the application of the proposed model to the flow experiment on another shale sample at higher pressure levels is in accordance with these observations. Interestingly, as temperature increases, the flow rate decreases with minor amplitudes. Under the conditions studied, the pressure change can cause over 10 times variation of the flow rate, revealing measures should be taken to maintain relatively high reservoir pressures to guarantee appreciable gas production from matrix if the other factors remain unchanged. In addition, the difference between the average flow shape in the whole rock and the gas motion in the pore of mean radius is revealed. Sounder in theoretical bases and better in application effects, the proposed model is expected to be of practical significance for guiding shale gas reservoir development. • A comprehensive flow mechanism scheme differing from com-mon re-search is proposed. • A new coupled flow model with deduced coupling coefficients is established. • A unified model, i.e. the macroscopic form of the new coupled model, is obtained. [ABSTRACT FROM AUTHOR]

The shale gas productivity model based on shale gas nonlinear seepage mechanism is an effective way to reasonably predict productivity. The incomplete gas nonlinear effects considered in the current production prediction models can lead to inaccurate production prediction. Based on the conventional five-zone compound flow model, comprehensive gas nonlinearities were considered in the improved compound linear flow model proposed in the paper and a semianalytical solution for productivity was obtained. The reliability of the productivity model was verified by the field data, and then, the 20-year production performance analysis of the gas well was studied. Ultimately, the key influencing factors of the fracture control stage and matrix control stage have been analyzed. Research indicated the following: (1) the EUR predicted by the productivity model is higher than the EUR that the comprehensive nonlinear effects are not considered, which demonstrated that the various nonlinear effects cannot be neglected during the production prediction to ensure the greater calculation accuracy; (2) during the early production stage of shale reservoir, the adsorbed gas is basically not recovered, and the cumulative adsorption contribution rate does not exceed 10%. The final adsorption gas contribution rate is 23.28%, and the annual adsorption rate can exceed 50% in the 20th year, showing that free gas and adsorbed gas are, respectively, important sources of the early stage of production and long-term stable production; (3) the widely ranged three-dimensional fracturing reformation of shale reservoirs and reasonable bottom hole pressure in the later matrix development process should be implemented to increase the effective early production of the reservoir and ensure the earlier gas production process of the matrix development. The findings of this study can help for better ensuring the prediction accuracy of the estimated ultimate recovery and understanding the main influencing factors of the dynamic performance of gas wells so as to provide a theoretical reference for production optimization and development plan formulation of the shale gas reservoirs. [ABSTRACT FROM AUTHOR]

Highlights • Systematic nano-scale effects are characterized by virtue of clearly defined layers. • The main reason for the variation law of Knudsen layer thickness is revealed. • The role of density gullies as "lubricant layers" is shown. • The role of gas-gas interactions in controlling molecular motion is evidenced. • Nano-scale effects on gas movability are displayed. Abstract As an unconventional natural gas resource, shale gas plays a significant role in satisfying increasing global energy demands. Because of the less costs and better repeatability of molecular simulation for nano-scale research, it's becoming a nice way to study the distribution and motion characteristics of shale gas, which is the key to get insights into the nano-scale effects in shale matrix. In this paper, pressure-dependent equilibrium molecular simulation of shale gas in organic-rich nano-slit is conducted, where the gas is divided into clearly defined layers and the structural and motion characteristics of different parts are detailedly analyzed, making systematic observations and descriptions of nano-scale effects happen. By virtue of this, the variation law of shale gas in the nano-slit and the mechanical theory behind it are proposed. Results also reveal the main reason for the roundabout ascension variation of Knudsen layer (KL) thickness, the role of density gullies as "lubricant layers" to enhance the diffusion in adsorption layers, the evidence of the role of gas-gas interactions in controlling molecular motion in addition to gas-wall interactions, nano-scale effects on gas movability with pressure from the viewpoint of gas development, etc. The physical phenomena caused by nano-scale effects and their variations with pressure in organic-rich nano-slit have been explicitly clarified, which is expected to be a useful reference for shale gas evaluation and exploitation. [ABSTRACT FROM AUTHOR]