TY  - JOUR
AU  - GAO, Yu
AU  - LUO, Ming
AU  - XIAO, Ping
AU  - FU, Qi
AU  - LI, Xin
AU  - HUANG, Honglin
AU  - HU, Yitao
AU  - JIANG, Bo
PY  - 2026
TI  - Drilling time and parameter optimization technology development based on big data analysis
JO  - Petroleum Science Bulletin
SN  - 2096-1693
SP  - 558
EP  - 580
VL  - 11
IS  - 2
AB  - To achieve integrated drilling acceleration in geological engineering, a drilling efficiency and parameter optimization system has been established. The system consists of three modules: data management and configuration, drilling efficiency management, and wellbore mechanical analysis with parameter optimization, enabling the visualized management of drilling operation efficiency. First, based on selected indicators from mud logging data, a “virtual best-performing well” model and an efficiency analysis chart were developed to optimize drilling efficiency and meet the engineering requirements of high penetration rates and low risks. Second, thorough investigation and modeling of formation fluid loss, wellbore structure, bottom-hole assembly, and drilling fluid properties in the target block were conducted to establish an optimal drilling model tailored to different formations. Meanwhile, a wellbore environment monitoring and evaluation model was built to provide early warning of operational risks. Application results demonstrate that the accuracy of drilling condition identification reaches 85%, reducing the drilling cycle by approximately 20%. This research contributes to cost reduction, efficiency improvement, and safe drilling operations, laying a foundation for the digital and intelligent development of the drilling industry.
UR  - https://doi.org/10.3969/j.issn.2096-1693.2026.03.009
DO  - 10.3969/j.issn.2096-1693.2026.03.009