five

Application of Rock Mechanics Algorithm to Optimize Drilling Rate of Penetration

收藏
Mendeley Data2024-01-31 更新2024-06-28 收录
下载链接:
http://doi.nrct.go.th/?page=resolve_doi&resolve_doi=10.14457/CU.the.2005.1720
下载链接
链接失效反馈
官方服务:
资源简介:
This study aims to generate predicted drilling rate of penetration (ROP) model based on rock mechanics algorithm concept in order to improve drilling performance in the Gulf of Thailand. The first step of the study is to determine the bit sliding coefficient value which is depended on particular selected drilling bit. This process of work utilized drilling and wireline logging data from an offset well to construct Rock Mechanics Algorithm (RMA) model with RMA software. After that, statistical analysis method is brought into this stage to facilitate in data matching result. The drilling optimization model is constructed in RMA model with an appropriate bit sliding coefficient value derived from the previous process. In this procedure, Unconfined Compressive Strength (UCS), Overburden pressure, Fluid pore pressure, and drilled & wireline log recorded are input into the program. Finally, Specific Energy Rate of Penetration (SEROP) which is a potential maximum ROP scheme is generated at each wellbore depth. Moreover, RMA model also shows the zone of high abrasivivity formation in order to adjust drilling parameters while drilling to maintain drilling bit life. On drilling rig site study, SEROP with recommended drilling parameters are oriented to actual drilling operation. The results show the improvement of average ROP comparing to an offset well. A single bit run to Target Depth (TD) is also one of the accomplish result from the bit life study. The major benefits are eliminating redundant drilling bit cost and drilling rig cost from tripping time. RMA model is a powerful tool using with Cost per Foot (CPF) analysis while conduct drilling operation or encounter critical ROP situation. Drilling RMA model is also helpful for the project well designer and cost estimator.
创建时间:
2024-01-31
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作