Study on the Application of Data Mining Technology Based on Support Vector Machine in the Database Management of Oil Exploration and Development

摘要

Mineral resources are national industrial base, the mining is difficult, the cycle is long, and if the decision is wrong, it will bring great losses to the state and enterprises. China has abundant mineral resources and a long mining history, and with the advance of industrializationand automation, physical and chemical indicators of each aspect are becoming increasingly sophisticated. However, how to conduct production guidance through the accumulated and ample physical and chemical indicators and to explore the potential value of the data is a major problem that shouldbe solved urgently by researchers and government policy makers. Among a number of physical and chemical indicators, provenance indicator plays an important instructive role in the proved rate of oil exploration and the discovery of potential exploration areas. This paper explores the provenanceof physical and chemical indicators based on the intelligent algorithm of support vector machine, determines the provenance distribution through its clustering rate and verifies the higher feasibility of the application of artificial intelligence in the development of oil field.