Decline Curve Analysis of Fractured Horizontal Wells Through Segmented Fracture Model

Qin, Jiazheng; Cheng, Shiqing; He, Youwei; Wang, Yang; Feng, Dong; Yang, Zhonglin; Li, Dingyi; Yu, Haiyang

doi:10.1115/1.4040533

Cited by 25 publications

(2 citation statements)

References 53 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…√𝑀𝑆𝐸 𝑌 𝑜𝑏𝑠,𝑚𝑎𝑥 −𝑌 𝑜𝑏𝑠,𝑚𝑖𝑛 (20) where 𝑌 𝑜𝑏𝑠,𝑚𝑎𝑥 is the maximum value of the measured data, and 𝑌 𝑜𝑏𝑠,𝑚𝑖𝑛 is the minimum value of the measured data. (21) where…”

Section: 𝑁𝑅𝑀𝑆𝐸 =mentioning

confidence: 99%

“…The gas percolation equation is linearized by replacing the original pressure and original time with the concepts of pseudo pressure and pseudo time. The Agarwal-Gardner method performs an instantaneous analysis of pressure changes and introduces a new dimensionless time definition based on the well control area, following the Blasingame method [21].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Research on Production Prediction Method of Multi-stage Fractured Shale Gas Horizontal Well

Yin,

Zhang

2024

Applied Mathematics and Nonlinear Sciences

View full text Add to dashboard Cite

Shale gas is a crucial component of unconventional energy. Productivity evaluation of gas wells is essential to ensure efficient and stable production. However, predicting productivity has been challenging due to the complex characteristics of shale gas reservoirs and the use of multi-stage fractured horizontal wells (MFHW) technology in the development process. This study compares traditional production prediction methods with an optimized least squares support vector machine model (LSSVM). The traditional productivity prediction method involves establishing a mathematical model of the MFHW in a fully enclosed rectangular shale formation. The model considers the effects of shale gas adsorption, diffusion, and pressure sensitivity. The model’s analytical solution is obtained using Duhamel’s principle, Laplace transform, and inverse transform. An independent production data analysis software is developed based on the analytical solution of bottom-hole pressure to predict production. To implement the LSSVM model, the model’s input parameters must be determined first. The LSSVM model’s regularization parameters and kernel parameters are obtained through the particle swarm optimization (PSO) algorithm, and the prediction model is established. The model’s matching is evaluated by calculating the coefficient of determination (R2) and the normalized root mean square error (NRMSE). The results indicate that the traditional production capacity prediction method is suitable for stable production in terms of applicability. However, the LSSVM model does not have this limitation and generally provides more accurate predictions throughout the entire production process. For complex shale gas reservoirs that frequently switch wells and use multi-stage fracturing technology, the LSSVM model is more suitable for predicting shale gas well productivity.

show abstract

Section: 𝑁𝑅𝑀𝑆𝐸 =mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Research on Production Prediction Method of Multi-stage Fractured Shale Gas Horizontal Well

Yin,

Zhang

2024

Applied Mathematics and Nonlinear Sciences

View full text Add to dashboard Cite

show abstract

A study of the mechanism of nonuniform production rate in shale gas based on nonradioactive gas tracer technology

Huang¹,

Li²,

Wu³

et al. 2020

Energy Science & Engineering

View full text Add to dashboard Cite

The performance of horizontal wells in shale gas is controlled by multiple factors, and there is a difference in gas production rate between different fracturing stages. However, the mechanism of the nonuniform gas production rate is still not clear. In this paper, a typical shale gas well in the Longmaxi formation was selected to conduct the performance evaluation based on the nonradioactive gas tracer technology. The gas production profile was obtained, and the production feature of each stage was analyzed. On this basis, the production differences between fracturing stages were compared in four aspects: reservoir physical properties, distribution of natural fracture, parameters of fracturing operation, and technology of temporary plugging re‐orientation. The effect of various factors on the contribution of each stage was analyzed. And then, the mechanism of the nonuniform gas production rate was clarified. Finally, relevance analysis was performed to determine the main controlling factors, and a mathematical model for characterizing the nonuniform gas production rate feature was established by adopting the nonlinear regression method. This study provides a reliable basis for optimal fracturing designing and reasonable production planning.

show abstract

A productivity prediction method for multi-fractured horizontal wells in tight oil reservoirs considering fracture closure

Gao

Guo

Chen

et al. 2022

J Petrol Explor Prod Technol

View full text Add to dashboard Cite

The closure fracture phenomenon increases the complexity of well testing and reduces the accuracy of productivity forecasts when tight oil reservoirs are exploited. However, most existing productivity models tend to ignore this. Therefore, a productivity prediction model for multi-fractured horizontal wells in tight oil reservoirs considering fracture closure has been developed by considering the stress sensitivity in the formation and combining the physical parameters of actual production. The model is solved by the Laplace transform, perturbation transform, Pedrosa transform, and Stehfest numerical inversion. Drawing productivity impact curves and discussing productivity influence factors based on the model results from this study show that the model is reasonable. In the actual production process, the hydraulic fracture parameter values are not as high as possible, and they have a reasonable range of values. The fracture closure pressure has a significant impact on the production of tight oil reservoirs. The higher the fracture closure pressure is, the greater the fracture conductivity decreases sharply, and the larger the proppant elastic modulus is, the stronger the fracture conductivity. The influence of fracture conductivity on the production in tight oil reservoirs has an obvious point, and when the value is less than the point, the production effect is good. Improved production can be achieved by balancing the relationship between fracture parameters. The findings of this study can help to better understand the influence of fracture parameters on productivity and contribute to increasing well production and improved development of tight oil reservoirs.

show abstract

Decline Curve Analysis of Fractured Horizontal Wells Through Segmented Fracture Model

Cited by 25 publications

References 53 publications

Research on Production Prediction Method of Multi-stage Fractured Shale Gas Horizontal Well

Research on Production Prediction Method of Multi-stage Fractured Shale Gas Horizontal Well

A study of the mechanism of nonuniform production rate in shale gas based on nonradioactive gas tracer technology

A productivity prediction method for multi-fractured horizontal wells in tight oil reservoirs considering fracture closure

Contact Info

Product

Resources

About