Theoretical Approach for the Calculation of the Pressure Drop in a Multibranch Horizontal Well with Variable Mass Transfer

Yue, Ping; Yang, Hongnan; He, Chuanjian; Yu, Gao; Sheng, James J.; Guo, Z L; Guo, Chunqiu; Chen, X F

doi:10.1021/acsomega.0c03971

Cited by 8 publications

(5 citation statements)

References 44 publications

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“…Furthermore, these statistical values in Table 7, as visualized in Figs. (7)(8), imply that the predictions of the developed neural-based models were closer to the actual Poettmann integral values for estimating static bottom-hole pressure. The assertion is because the estimated statistical indicators MAE, ARE, AARE, MSE, and RMSE values were far less than 1, as visible in Figs.…”

Section: Comparison Of the Developed Neural-based Models Predictions ...mentioning

confidence: 64%

“…The assertion is because the estimated statistical indicators MAE, ARE, AARE, MSE, and RMSE values were far less than 1, as visible in Figs. (7)(8).…”

Section: Comparison Of the Developed Neural-based Models Predictions ...mentioning

confidence: 99%

“…Historically, BHP data have been obtained by direct measurements with a downhole gauge [6,7]. As a result, there is much redundancy due to mechanical failure of the downhole equipment [8]. However, it is not economical or practical to obtain BHP data from drilling equipment (pressure sensors) [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

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Interpretation of Neural Network Models – New Insights of Estimating Static Bottom-Hole Pressures of Gas Wells in Nigerian Petroleum Provinces

Udoma,

Okon,

Udoeyop

et al. 2023

Int. J. Petrol. Technol.

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Methods to determine static bottom-hole pressure (BHP) from surface measurements include the average temperature and z-factor method, the Sukkar-Cornell method, the Cullender-Smith method, and the Poettmann method. Among these methods, the Poettmann method is preferable in the petroleum industry but with a concern for software developers, as the integral values to determine the static BHP are tabular. In this study, neural network-based models to predict the integral values using pseudo-reduced pressures and temperatures were developed. The 2-3-1, 2-4-1, and 2-5-1 neural-based models had overall correlation coefficients (R) of 0.9974, 0.99835, and 0.99745, respectively, for the maximum-minimum normalization method and R of 0.99745, 0.99805, and 0.9992 for the clip-scaling method. Comparing the models' predictions with the Lagrangian interpolated values resulted in R of 0.99895 and 0.9995 for the maximum-minimum and clip-scaling-based models. Thus, the developed models can predict Poettmann's integral values without table look-up to estimate static BHP in gas wells.

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Section: Comparison Of the Developed Neural-based Models Predictions ...mentioning

confidence: 64%

“…The assertion is because the estimated statistical indicators MAE, ARE, AARE, MSE, and RMSE values were far less than 1, as visible in Figs. (7)(8).…”

Section: Comparison Of the Developed Neural-based Models Predictions ...mentioning

confidence: 99%

See 1 more Smart Citation

Interpretation of Neural Network Models – New Insights of Estimating Static Bottom-Hole Pressures of Gas Wells in Nigerian Petroleum Provinces

Udoma,

Okon,

Udoeyop

et al. 2023

Int. J. Petrol. Technol.

View full text Add to dashboard Cite

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“…Therefore, the Newton-Raphson method is used for iterative solution. The Newton-Raphson method has many advantages, such as efficiency and fast convergence, and it has shown good application effects in wellbore modeling [22][23][24].…”

Section: Newton-raphson Iterationmentioning

confidence: 99%

A Novel Geothermal Wellbore Model Based on the Drift-Flux Approach

Yuan,

Li,

Zhang

et al. 2024

Preprint

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Geothermal energy, being a clean energy source, has immense potential, and accurate wellbore modeling is crucial for optimizing the drilling process and ensuring safety. This paper presents a novel geothermal wellbore model based on the drift-flux approach, tested under three different temperature and pressure well conditions. The proposed model integrates the conservation equations of mass, momentum, and energy, incorporating the gas-liquid two-phase flow drift-flux model and heat transfer model. Key features include handling heat transfer between the for-mation and the wellbore, addressing the slip relationship between gas and liquid phases, and accounting for wellbore friction. The nonlinear equations are discretized using the finite differ-ence method, and the highly nonlinear system is solved using the Newton-Raphson method. Numerical simulation, validation, and comparison with existing models demonstrate the en-hanced accuracy of this model. In our tests, the model achieved high accuracy in calculating bottom hole pressure and temperature, with Mean Relative Errors (MRE) significantly lower than those of other models. These results offer valuable insights for optimizing drilling parameters and ensuring drilling safety. Comparisons indicate that this approach significantly outperforms others in capturing the complex dynamics of geothermal wellbores, making it a superior tool for geo-thermal energy development.

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“…Gladkikh and Wu 29 used the finite element method to establish a herringbone well productivity model with perforating completion and studied the effect of perforating parameters on productivity. Yue 30 focused on the pressure drop in the wellbore, established the herringbone well productivity model, and analyzed the sensitive factors of productivity, but for the evaluation of production based on the steady flow, the production time was not considered. At present, the study on transient productivity and its influence on perforated herringbone wells is less.…”

Section: Introductionmentioning

confidence: 99%

Transient Productivity Analysis and Completion Parameter Optimization of Perforating Herringbone Wells

et al. 2023

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Herringbone wells are of great significance in tapping the potential of remaining reservoirs, improving recovery efficiency, and reducing development costs and have been widely used in oilfields, especially offshore oilfields. Due to the complex structure of herringbone wells, there is mutual interference between wellbores during seepage, resulting in complex seepage problems, and it is difficult to analyze the productivity and evaluate the perforating effect. In this paper, considering the mutual interference between branches and perforations, a prediction model of transient productivity of perforated herringbone wells was derived based on the theory of transient seepage, and the complex structure with any number of branches, arbitrary configurations, and orientations in three-dimensional space could be considered in this model. The formation pressure in reservoir points at different production times, IPR curves, and the radial inflow of herringbone well were studied by the line-source superposition method, which directly reflected the process of productivity and pressure change, avoiding the one-sidedness caused by using a point source to replace the line source in the stability analysis. Then, through the productivity calculation of different perforation schemes, the influence curves of perforation density, perforation length, perforation phase angle, and perforation radius on unstable productivity were obtained. Orthogonal tests were performed to obtain the degree of impact of each parameter on productivity. Lastly, the selective completion perforation technology was adopted. When the shot density at the end of the wellbore was increased, the productivity of herringbone wells could be improved economically and effectively. According to the above study, a scientific and reasonable construction scheme is recommended for oil well completion construction, which provides a theoretical basis for the improvement and development of perforation completion technology.

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Theoretical Approach for the Calculation of the Pressure Drop in a Multibranch Horizontal Well with Variable Mass Transfer

Cited by 8 publications

References 44 publications

Interpretation of Neural Network Models – New Insights of Estimating Static Bottom-Hole Pressures of Gas Wells in Nigerian Petroleum Provinces

Interpretation of Neural Network Models – New Insights of Estimating Static Bottom-Hole Pressures of Gas Wells in Nigerian Petroleum Provinces

A Novel Geothermal Wellbore Model Based on the Drift-Flux Approach

Transient Productivity Analysis and Completion Parameter Optimization of Perforating Herringbone Wells

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