Interwell connectivity identification in immiscible gas-oil systems using statistical method and modified capacitance-resistance model: A comparative study

Yousefi, Seyed Hamidreza; Rashidi, Fariborz; Sharifi, Mohammad; Soroush, Mohammad; Ghahfarokhi, Ashkan Jahanbani

doi:10.1016/j.petrol.2020.108175

Cited by 16 publications

(3 citation statements)

References 39 publications

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“…Study on IWC in oil reservoirs encompasses predicting the daily oil production of producing wells, quantitative description of IWC, and analysis of dynamic changes [1]. Traditional IWC study methods typically involve tracer testing, pressure testing, well testing, and other complex and costly means [2]. In order to overcome these drawbacks, scholars have established mathematicalphysical models for IWC analysis, utilizing static and dynamic parameters and production measures derived from oilfield production data.…”

Section: Introductionmentioning

confidence: 99%

An Interwell Connectivity Assessment Model for Polymer Flooding Short-Term Development Data Based on A-LSTM and EFAST Methods

Li,

Zhang,

Tan

et al. 2024

International Journal of Energy Research

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Interwell connectivity assessment in polymer-driven reservoirs is critical for setting appropriate injection rates and improving oil recovery. Traditional deep learning techniques often lack accuracy and reliability when applied to short-term oilfield production data. In response, the A-LSTM algorithm is proposed, which integrates the attention mechanism with a long- and short-term memory network (LSTM). The predictive accuracy of A-LSTM is assessed and juxtaposed with LSTM and support vector regression (SVR) algorithms for short-term single-well daily oil production analysis. The Huber loss function was utilized to quantify the difference between predicted and actual results, resulting in a dynamic production prediction model. An interwell connectivity (IWC) assessment model is then obtained by fusing the dynamic production prediction model with the EFAST method, thus demonstrating the superior prediction accuracy of A-LSTM in oil production prediction and connectivity assessment. Moreover, the credibility of the assessment is further corroborated through numerical simulations and interwell tracer tests. The study results showed that the interwell connectivity evaluation model based on the A-LSTM algorithm and EFAST method is not only capable of accurately predicting the single-well daily oil production using a small sample dataset but also a highly reliable method for interwell connectivity evaluation, and the application of the interwell connectivity assessment model can further guide polymer flooding work in oilfields.

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Section: Introductionmentioning

confidence: 99%

An Interwell Connectivity Assessment Model for Polymer Flooding Short-Term Development Data Based on A-LSTM and EFAST Methods

Li,

Zhang,

Tan

et al. 2024

International Journal of Energy Research

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“…For example, a combination of the hybrid genetic algorithm, particle swarm optimization (PSO), and streamline-based reservoir simulation (Naderi, 2021 [13]; Azamipour, 2018 [14], 2023 [15]) has been studied. Furthermore, the reservoir is also approximated as a multi-well injection-production system, and capacitance and resistant models (Yousef, 2006 [16]; Soroush, 2014 [17]; Yousefi, 2020 [18]; Huang, 2023 [19]; Guo, 2023 [20]), system analysis models (Liu, 2009 [21]), and INSIM-derived models (Zhao, 2014 [22], 2016 [23], 2019 [24], 2022 [25]) have been developed to predict and optimize inter-well connectivity and the water-injection rate.…”

Section: Introductionmentioning

confidence: 99%

A New Method for Optimizing Water-Flooding Strategies in Multi-Layer Sandstone Reservoirs

Guo,

Yang,

Zhao

et al. 2024

Energies

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As one of the most important and economically enhanced oil-recovery technologies, water flooding has been applied in various oilfields worldwide for nearly a century. Stratified water injection is the key to improving water-flooding performance. In water flooding, the water-injection rate is normally optimized based on the reservoir permeability and thickness. However, this strategy is not applicable after oilfields enter the ultra-high-water-cut period. In this study, an original method for optimizing water-flooding parameters for developing multi-layer sandstone reservoirs in the entire flooding process and in a given period is proposed based on reservoir engineering theory and optimization technology. Meanwhile, optimization mathematical models that yield maximum oil recovery or net present value (NPV) are developed. The new method is verified by water-flooding experiments using Berea cores. The results show that using the method developed in this study can increase the total oil recovery by approximately 3 percent compared with the traditional method using the same water-injection amounts. The experimental results are consistent with the results from theoretical analysis. Moreover, this study shows that the geological reserves of each layer and the relative permeability curves have the greatest influence on the optimized water-injection rate, rather than the reservoir properties, which are the primary consideration in a traditional optimization method. The method developed in this study could not only be implemented in a newly developed oilfield but also could be used in a mature oilfield that has been developed for years. However, this study also shows that using the optimized water injection at an earlier stage will provide better EOR performance.

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“…Their method successfully quantified the flow resistance between capacitance, productivity index (PI) and well pairs. In 2021, Yousefi et al [25] modified capacitance-resistance model (or M-CRM as a physical approach) through the combination of least square support vector machine and multiple linear regression (as a statistical approach) which are utilized for two immiscible gas injection cases. In these cases, the interwell connectivity is predicted and producer total rate is estimate.…”

Section: Introductionmentioning

confidence: 99%

A Model for the Connectivity of Horizontal Wells in Water-Flooding Oil Reservoirs

Shi¹,

Meng²,

Zhang³

et al. 2022

Fluid Dynamics &Amp; Materials Processing

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As current calculation models for inter-well connectivity in oilfields can only account for vertical wells, an updated model is elaborated here that can predict the future production performance and evaluate the connectivity of horizontal wells (or horizontal and vertical wells). In this model, the injection-production system of the considered reservoir is simplified and represented with many connected units. Moreover, the horizontal well is modeled with multiple connected wells without considering the pressure loss in the horizontal direction. With this approach, the production performance for both injection and production wells can be obtained by calculating the bottom-hole flowing pressure and oil/water saturation according to the material balance equation and a saturation front-tracking equation. Some effort is also provided to optimize (to fit known historical production performances) the two characteristic problem parameters, namely, the interwell conductivity and connected volume by means of a SPSA gradient-free algorithm. In order to verify the validity of the model, considering a heterogenous reservoir, three conceptual examples are constructed, where the number ratio between injection and production wells are 1/4, 4/1 and 4/5, respectively. It is shown that there is a high consistency between simulation results and field data.

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Interwell connectivity identification in immiscible gas-oil systems using statistical method and modified capacitance-resistance model: A comparative study

Cited by 16 publications

References 39 publications

An Interwell Connectivity Assessment Model for Polymer Flooding Short-Term Development Data Based on A-LSTM and EFAST Methods

An Interwell Connectivity Assessment Model for Polymer Flooding Short-Term Development Data Based on A-LSTM and EFAST Methods

A New Method for Optimizing Water-Flooding Strategies in Multi-Layer Sandstone Reservoirs

A Model for the Connectivity of Horizontal Wells in Water-Flooding Oil Reservoirs

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