基于改进遗传算法的钻井参数优选方法研究  

Drilling Parameter Optimization Based on Advanced Genetic Algorithm

作　　者：景宁 蒋璐朦 耿智[3] 邓丽超 

机构地区：[1]中油国际(乍得)有限责任公司 [2]中国石油天然气勘探开发公司 [3]中国石油大学(北京) [4]中石油昆仑燃气有限公司(涿州)

出　　处：《石油机械》2016年第1期10-15,共6页China Petroleum Machinery

基　　金：国家科技重大专项"钻井工程技术和工艺软件"(2011ZX05021-006)的部分研究成果

摘　　要：为改善自适应遗传算法局部寻优精度较差的缺陷,提出基于模式搜索的遗传混合算法。在自适应遗传算法的基础上,对进化种群进行模式搜索寻优,使得该混合算法既具有较强的全局搜索能力,又提高了局部寻优精度。以钻井过程中单位进尺成本作为目标函数,以克拉玛依地区已钻井为例对算法进行验证,计算结果表明,该井优化钻压比实际钻压平均值略高;而优化转速与实际钻速平均值相差不大;优化钻头磨损量比实际使用钻头磨损量高,提高钻头使用率能够在一定程度上降低钻井米成本,提高钻井经济效益。研究结果可为制定钻井设计方案提供依据。To address the defect of poor local optimization precision for adaptive genetic algorithm,the genetic hybrid algorithm based on pattern search is proposed. Based on adaptive genetic algorithm,the pattern search optimization of the evolutionary population makes the hybrid algorithm has strong global search ability,and improves the precision of local optimization. Making the cost per meter in the process of drilling as objective function,taking the drilled well in Karamay as an example to verify this algorithm,the calculation results show that the optimized WOB slightly higher than the practical average WOB; the optimized RPM is almost the same with the practical average RPM; the optimized drill bit wear is higher than the practical bit wear. Improved drill bit usage could,in certain extent,reduce the cost of per meter,improving the economic efficiency of drilling.

关 键 词：遗传算法 模式搜索 钻井工程 参数优选 

分 类 号：TE22[石油与天然气工程—油气井工程]