Abstract

Based on a large number of empirical statistics of tertiary oil recovery technology in China, including polymer flooding, chemical flooding, gas flooding, in situ combustion, steam flooding, ect., 22 key reservoir parameters were filterized. Five levels of quantitative screening criteria were developed for different tertiary oil recovery methods. The mean algorithm for the downward approximation and the grey correlation theory were used in this paper to quickly select the appropriate tertiary oil recovery method for the target blocks, which provides a preferred development method for subsequent potential evaluation. In the rapid analogy evaluation method of tertiary oil recovery potential, the total similarity ratio between the target block and the example block is determined. The target block is matched with the appropriate instance block according to the total similarity ratio value, using 80% as the boundary. The ratio of the geological reserves is used to predict the oil recovery interval, the actual annual injection data, and the economic profit, thus quickly predicting the economic potential of the tertiary oil recovery technology in the target block. Currently, our research team has integrated these two methods into the tertiary oil production potential evaluation software EORSYS3.0. The empirical analysis shows that this method is reasonable and the conclusion is reliable. In addition, the actual enhanced recovery value is within the effective range predicted by the method. The method and results of this paper will provide an important decision-making reference for the application and sustainable development of China Petroleum’s main tertiary oil recovery technology in the next 5–10 years.

Highlights

  • All countries in the world actively carry out technical research and the application of enhanced oil recovery according to the characteristics of their own oil national reservoirs [1,2]

  • Combined with the present situation and trend of tertiary oil recovery technology and the classification standards formulated by various oil fields and industries, 22 specific reservoir parameters were selected as the key classification indicators, based on the main reservoir and fluid characteristic parameters of typical field tests

  • The rapid analogy evaluation model of the tertiary oil recovery potential is mainly used to calculate the similarity between the evaluation block and the example block by the fuzzy grey correlation method, by judging the similarity or dissimilarity of the changes between the parameters, so that the screening evaluation block is suitable for the tertiary oil recovery method

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Summary

Introduction

All countries in the world actively carry out technical research and the application of enhanced oil recovery according to the characteristics of their own oil national reservoirs [1,2]. Since 1996, there has been chemical compound flooding [5,6], CO2 miscible flooding [7], gas injection immiscible flooding, thermal recovery, ect This was supplemented by the Petroleum Exploration and Development Institute, who compiled the corresponding economic potential evaluation software. Since 1998, the third potential evaluation has been carried out in China This evaluation is of great significance for the standardization of the third oil recovery and the formulation of medium - and long-term development strategies [9,10,11,12,13,14,15]. The integrated software of the potential evaluation and economic evaluation with a high integration degree, perfect function, and independent intellectual property rights are developed according to this method, which provides good technical support for the work of the tertiary oil recovery potential evaluation

Fine Quantitative Screening Method for Tertiary Oil Recovery Technology
Fine Quantitative Screening Model Establishment
Fine Quantitative Screening Standard Setting
Fine Quantitative Screening Method Flow
Rapid Analogy Evaluation Method for Tertiary Oil Recovery Potential
Rapid Analogy Evaluation Model
Rapid Analogy Potential Evaluation Process
Recovery Prediction
Potential Prediction
Software Development and Case Analysis
Comprehensive Score Results
Conclusions
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