首页|A method of predicting oil and gas resource spatial distribution based on Bayesian network and its application
A method of predicting oil and gas resource spatial distribution based on Bayesian network and its application
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The spatial distribution prediction of hydrocarbon resource is essential to reduce exploration risks and improve investment returns.Determining the location of the spatial distribution of oil and gas resources is a complex and uncertain problem.This paper systematically analyzes oil and gas exploration risk assessment and resource spatial distribution prediction technology,and proposes a method of predicting hydrocarbon spatial distribution based on averaged one-dependence estimators(AODE).Firstly,the transformation process of petroleum geological problem to mathematical model is described.Then,the classification principle and decision rule of AODE model are expounded.Finally,a case study of Sangonghe Formation in the hinterland of Junggar Basin in China is given to further illustrate the proposed method and work flow.The case prediction results not only reveal that the accuracy of the AODE model can reach 85.2% on the data set of 203 exploratory wells,which is higher than state-of-the-art methods(such as tree augmented Bayesian network method and the Mahalanobis distance method),but also point out the areas witii high probability of remaining hydrocarbon resources in Sangonghe Formation,which provides decision-making basis for the next exploration.The application results show that the AODE model can effectively predict the spatial distribution of oil and gas and visualize the risk of geological exploration,thereby optimizing drilling strategy and increasing economic benefits.
Petroleum resourcesSpatial distribution predictionBayesian networkAODE modelSangonghe FormationJunggar Basin
Qiulin Guo、Hongjia Ren、Jingdu Yu
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Research Institute of Petroleum Exploration & Development,PetroChina,Beijing,100083,China
College of Computer Science and Technology,Jilin University,Changchun,130012,China
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