Southwest Petroleum University

Yuehao Liu

Xiangchao Shi

Yuming Wang

Yan Chen

Yang Wang

Ping Li

Yuan Zhong

Hu Deng

Shan Jiang

Yuchuan An

Gaocheng Feng

Yu Yi

Yangbing Li

Zhicheng Li

Ergang Zhang

Ming Xian

Quan Cao

The present invention relates to a method for predicting and optimizing a penetration rate in oil and gas drilling based on a CART algorithm. The method provided by the present invention can shorten the drilling cycle and reduce the drilling cost, thereby greatly improving the development efficiency of oil and gas resources.

Method for predicting and optimizing penetration rate in oil and gas drilling based on cart algorithm

A method for predicting and optimizing an ROP for oil and gas drilling based on Bayesian optimization includes: acquiring raw drilling data according to a preset sampling period, constructing an initial sample data set based on the raw drilling data, constructing an ROP prediction model based on the initial sample data set, and predicting an ROP at a next sample point through a Gaussian process regression based on the ROP prediction model. The present invention realizes rapid analysis of historical drilling data and accurate prediction of an ROP range at a sample point in a feasible domain. The method can obtain an optimized ROP and an optimized engineering parameter through Bayesian optimization, and obtain an engineering parameter corresponding to an optimal ROP. The method has few restrictions on the drilling engineering parameter and the raw formation parameter, improves prediction accuracy, and avoids the problem of blurred parameter value boundaries.

Method for predicting and optimizing rate of penetration (ROP) for oil and gas drilling based on bayesian optimization

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Chengdu, China

Yuehao Liu