Study on Pulse Characteristic of Produced Crude Composition in CO<sub>2</sub> Flooding Pilot Test

Precise forecasting of Gas-Oil Ratio (GOR) curves is crucial for the effective and safe exploitation of reservoirs influenced by CO2 flooding. On a macroscopic level, the GOR curve typically exhibits a rapid rise, while on a microscopic level, it shows significant fluctuations. These characteristics make it challenging for conventional prediction methods to capture these dynamics, resulting in notable deficiencies in existing univariate models in terms of rapid response to changes and anomaly detection. To address the challenges in predicting GOR curves, this study employs impulse response functions and cross-correlation functions to identify the lagged correlation between water cut and GOR curves. Based on these findings, a prediction strategy incorporating water cut constraints is proposed. This approach utilizes a multi-input Long Short-Term Memory (LSTM) network to balance the long-term trends and short-term fluctuations in GOR. The model is trained on well production data from 26 production wells in a CO2 pilot area in Northeast China, capturing monthly production indicators to improve prediction accuracy and enhance early warning capabilities for CO2 breakthrough events. The research results indicate that incorporating water cut as a constraint variable significantly improved the accuracy of GOR curve predictions, particularly enabling predictions 60 days in advance in multi-step forecasting. The model's mean absolute error (MAE) decreased from 260.60 to 172.89, and the root mean square error (RMSE) reduced from 522.87 to 382.15, demonstrating a significant enhancement in the model's prediction accuracy and performance. Incorporating water cut as a constraint variable into the deep learning prediction strategy significantly improves GOR curve trend accuracy and sensitivity to fluctuations. This provides engineers with an early warning tool for CO2 breakthrough events, reducing uncertainty and risk in CO2 injection. Additionally, introducing lagged correlation variables enhances the model's ability to capture complex interactions in time series data, offering valuable insights and methodological references for future productivity prediction research.

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Research on the Timing of WAG Intervention in Low Permeability Reservoir CO2 Flooding Process to Improve CO2 Performance and Enhance Recovery

Zhao,

Sang,

Ding

et al. 2023

Energies

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In low permeability reservoirs, CO2 flooding usually leads to gas channeling, whereby a significant amount of CO2 bypasses the oil-bearing formation and fails to effectively displace oil. Introducing water-alternating-gas (WAG) flooding, utilizing water phase stability-driven processes, serves to suppress gas channeling and enhance oil recovery rates. Implementing WAG flooding, which utilizes water phase stability-driven processes, helps suppress gas channeling and improve oil recovery rates. The timing of implementing WAG flooding is crucial. Initiating WAG flooding prematurely can limit the efficiency of CO2 displacement, while initiating it with delays may result in severe gas channeling, resulting in decreased production and increased environmental risks. Finding the balance point is the challenge. The balance point can effectively control gas channeling without reducing the efficiency of CO2 flooding. In this paper, the timing of WAG flooding in low permeability reservoirs is studied in detail. Firstly, this study conducted experimental research to investigate the CO2 displacement process in both homogeneous and heterogeneous cores. Furthermore, it validated the correlation between the timing of WAG injection and the heterogeneity of the cores. The experimental results indicated the existence of an optimal timing for WAG injection, which is correlated with the degree of heterogeneity. Numerical simulation studies were performed to simulate the characteristics of the light oil–CO2 system using the Peng–Robinson (PR) equation. Furthermore, a history matching analysis was performed to validate the experimental results and investigate the correlation between WAG injection and the degree of heterogeneity. The study concluded that as the degree of heterogeneity increases, initiating WAG injection earlier leads to a more significant suppression of gas channeling, increased water–gas interaction, improved gas–oil contact, and enhanced the synergistic effect of increasing the resistance and pressure of WAG flooding and controlling gas channeling. This finding has significant practical implications, as the optimization of WAG injection timing can enhance oilfield production efficiency.

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Study on Pulse Characteristic of Produced Crude Composition in CO₂ Flooding Pilot Test

Cited by 3 publications

References 13 publications

Water-saturated CO2 injection in a carbonate rock – Effect of pore heterogeneity

Water-saturated CO2 injection in a carbonate rock – Effect of pore heterogeneity

Mechanism of Water Cut Reduction in CO2 Flooding to Enhance GOR Curve Prediction Accuracy

Research on the Timing of WAG Intervention in Low Permeability Reservoir CO2 Flooding Process to Improve CO2 Performance and Enhance Recovery

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Study on Pulse Characteristic of Produced Crude Composition in CO2 Flooding Pilot Test

Cited by 3 publications

References 13 publications

Water-saturated CO2 injection in a carbonate rock – Effect of pore heterogeneity

Water-saturated CO2 injection in a carbonate rock – Effect of pore heterogeneity

Mechanism of Water Cut Reduction in CO2 Flooding to Enhance GOR Curve Prediction Accuracy

Research on the Timing of WAG Intervention in Low Permeability Reservoir CO2 Flooding Process to Improve CO2 Performance and Enhance Recovery

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Product

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Study on Pulse Characteristic of Produced Crude Composition in CO₂ Flooding Pilot Test