Southwest Petroleum University

Yuming Wang

Xiangchao Shi

Yuehao Liu

Jianfeng Liu

Yan Chen

Yang Wang

Ping Li

Yuan Zhong

Hao Yu

Hu Deng

Yuting Dai

Ming Xian

Shuanggui Li

Leiyu Gao

Yangbing Li

Xiuping Chen

Zhicheng Li

Qingling Li

Ergang Zhang

Quan Cao

Gaocheng Feng

Shan Jiang

Yuchuan An

Yu Yi

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

The present disclosure discloses a method for calculating a safe drilling fluid density in a fractured formation, including the following steps: S, performing image processing to identify a downhole fracture; S, establishing three-dimensional (3D) geological models based on parameters of the downhole fracture, and establishing a drilling wellbore model based on a size and length of a wellbore; S, assigning the model with material parameters, boundary conditions, and upper and lower bounds of an initial drilling fluid density, and calculating accuracy; S, solving the 3D geological models using a 3-dimension distinct element code (3DEC) and determining stability of a well wall; S, determining upper and lower bounds of a drilling fluid density using dichotomy; S, repeating steps Sto S; and S, after set accuracy conditions are reached, saving and outputting the safe drilling fluid density.

Method for calculating safe drilling fluid density in fractured formation

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

Yuming Wang