Research On Classification And Economic Evaluation Of Oilfield Difficult Mining Reserves

With the increasing scarcity of oil resources in our country, many oilfield development projects are turning to difficult mining reserves of low porosity and low permeability. It is necessary to evaluate effects of oilfield exploitation and economic benefits carefully because of the technology risks and economic risks in the development of difficult mining reserves. However, in face of complex oil field explorations and development conditions, oilfield projects workers are only able to give the classification of a single reservoir and physical indicators on the basis of the existing evaluation standards, but not able to give comprehensive evaluation of reserves. In generally speaking, they couldn’t fully excavete the existing exploration and development information while depending on the subjective experiences and judgments in the absence of comprehensive evaluation index system, not to mention reflecting the economic evaluation of development blocks accurately. Therefore, according to the principles of comprehensiveness, data integrity, data not average, weak correlation, fairness, strong explanatory principle, the dissertation constructs the evaluation index system of reserves classification, with the index containing development effect, block attribute, economic evaluation. Then this dissertation establishes combination empowerment model to calculate weight of the block attribute index, designs FCM algorithm to determine classification of the development effects of the developed blocks, and builds the undeveloped block classification method combining the FCM classification results with combined empowerment model, BP neural network algorithm, discriminant analysis method. Finally economic evaluation method of reflecting output attenuation effects is proposed according to the development project evaluations of undeveloped blocks. In the process of research, the dissertation always takes more than40blocks of an oilfield in Daqing as an example to explain the application process of difficult reserves classification and economic evaluation method, which obtaines good results.First of all, the dissertation combines classification of difficult reserves with the current situations and problems of evaluation to illustrate background of selected topic and concluding realistic and theoretical significance of research.Secondly, the dissertation reviews current research situation relevant research status of classification of difficult reserves and evaluation methods, and puts forward research goals and routes.Thirdly, this dissertation puts forward six principles of the comprehensiveness of evaluation index of reserves classification, data integrity, data not average, weak correlation of index, fairness, and strong explanatory, and establishes preliminary classification evaluation index system according to the comprehensive and data integrity. Then the dissertation screenings indicators under some principles of data not average, weak correlation of index, fairness and strong explanatory and the combination of experts’ advices with research situations. Index system involves three parts of the development effects, block attributes, economic evaluations, its role is to make full use of the relationship between information mining development effects of the developed blocks and attribute indexs, through which we can use the attribute index of undeveloped blocks and predict undeveloped block categories.Fourthly, this dissertation designes a fuzzy c-means (FCM) algorithm, classifying effect indicators of developed blocks, so as to determine the types of development effects and effects of each category features.we apply this method to the development effect classification of more than30developed blocks in certain oilfield Yu Daqing.Fifthly, this dissertation builds the combination empowerment model to measure the weights of various properties indexes in evaluating effect index. The model depends on sample datas of developed blocks, meanwhile, the objective function asks experts’ predict error and sample data error minimized. So the weighted prediction method combines existing objective sample datas of the blocks and experts’ experiences. We take blocks in certain oilfield in Daqing as an example to demonstrate the application of the model.Sixthly, on the basis of FCM classification of the development effect in the developed blocks, respectively, we use the BP neural network, combination empowerment model, discriminant analysis tools and so on to construct classification method of difficult reserves in the undeveloped blocks.This method fully excavates sample datas of developed blocks, put forward classification method of combination "effect index" with " index of geology and reservoir property", improves the traditional reserves classification method which relies on the subjective judgment and classification of geology, reservoir physical property indexes in the case of lacking" mining effect " in undeveloped block. We take blocks in certain oilfield in Daqing as an example to demonstrate the application of the classification method.Sevenly, the dissertation constructs economic evaluation methods of the difficult mining reserves of undeveloped blocks and predictes single well production and development costs on the basis of classification results. Then simulate time-production curve and translate Production of the first three months single well into corrected production of each evaluation period to predict cash flow of undeveloped blocks, and calculate the economic evaluation, then changes in sensitivity of development projects. This method makes effective use of the existing sample information of developed blocks, reflects the attenuation effect of oil field production and provides the economic evaluation methods of the oilfield development of undeveloped blocks.We take blocks in certain oilfield in Daqing as an example to demonstrate the application of the classification method.Finally, the dissertation makes a summary on the research contents and conclusions. Moreover, directions and prospects in the future research worthy of deep-going study are given.