Rate of Penetration Optimization and Prediction Based on a Geological Label-Parameter Spectrum Framework
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摘要: 针对钻井过程中钻速预测与优化面临的参数耦合复杂、地层描述粗糙、模型可解释性差等挑战，旨在实现地质驱动的钻进参数智能优化. 提出一种融合地质特征量化与多参数可视化分析的“地质标签-参数图谱”体系. 基于南海某区块实际数据，引入因子分析将该区域的深度、压力、地震波速、岩性等多源地质参数降维为3个公共因子，据此构建12类具有明确物理意义的地质标签. 基于地质标签与目标钻速区间的钻进参数图谱，直观展示不同地质条件下十余项工程参数的合理取值范围与最佳值. 基于图谱，可在实钻中通过比对参数曲线与图谱偏离，制定定量的参数优化策略；在设计阶段通过计算参数与多套图谱的匹配概率，实现钻速区间定量预测.Abstract: In response to the challenges of complex parameter coupling, rough formation description, and poor model interpretability in predicting and optimizing the rate of penetration (ROP) during drilling, this study aims to achieve geology-driven intelligent optimization of drilling parameters. A "Geological Label-Parameter Atlas" system integrating geological feature quantification and multi-parameter visualization analysis is proposed. Based on actual data from a block in the South China Sea, factor analysis is introduced to reduce multiple geological parameters, such as depth, pressure, seismic wave velocity, and lithology, into three common factors. Accordingly, 12 types of geological labels with clear physical meanings are constructed. The drilling parameter atlas, developed based on these geological labels and target ROP intervals, visually displays the reasonable value ranges and optimal values for over ten engineering parameters under different geological conditions. Based on this atlas, quantitative parameter optimization strategies can be formulated during actual drilling by comparing the deviation between current parameter curves and the atlas, while in the design stage, quantitative prediction of ROP intervals can be achieved by calculating the matching probability between design parameters and multiple sets of atlas.
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Key words:
- geological label /
- drilling parameter /
- ROP optimization and adjustment /
- ROP prediction /
- drilling
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图 1 受钻井液柱影响下的钻速突降工况
a，b. 分析区域内钻速突降实例；c. 钻速、钻井液柱压力与井深对比
Fig. 1. ROP sudden drop condition affected by drilling fluid column
图 2 区域地层统计
a. 分析区域地震波速统计；b. 分析区域地层压力统计；c. 分析区域地层类型统计
Fig. 2. Stratigraphic statistics in the area
图 7 本区域中不同地质标签数据量分布
Fig. 7. Data distribution of different geological labels in the area
图 8 钻进参数图谱建立流程（a）与实例（b）
Fig. 8. Establishment process of the drilling parameter atlas (a) and the example (b)
图 9 相同钻速条件下不同地质标签钻进参数图谱
a. 钻速ROP≤10 m/h时参数图谱；b. 钻速ROP≥30 m/h时参数图谱
Fig. 9. The drilling parameters atlas under the same ROP conditions and different geological labels
图 10 相同地质标签条件下不同钻速钻进参数图谱对比
a，b，c. 1，2，5号地质标签不同钻速范围内的钻进参数图谱
Fig. 10. Comparison of drilling parameters atlas with the same geological labels and different ROP
图 11 基于图谱的钻进参数优化调整示例
Fig. 11. Example of drilling parameter optimization based on the atlas
图 12 不同工况下钻速预测概率计算
左. 单参数概率赋值示意；右. 1号地质标签不同工况下钻速概率区间预测
Fig. 12. Prediction probability calculation of the ROP with different conditions
图 13 结合地质标签的参数图谱建立-使用流程
Fig. 13. Establishment and application workflow of geological label-parameter spectrum framework
表 1 采集参数类型列表
Table 1. List of parameter types
参数类型 参数名称/缩写 施工工艺 钻速/ROP；钻压/WOB；转速/RPM；扭矩/T；泵压/SPP；泵量/Q 钻井液性质 密度/MW；屈服值/YP；漏斗粘度/MV；塑性粘度/PV；滤失量/FL；PH；固相含量/SO 地质情况 深度/D；地震速度/EV；孔隙压力/PP；破裂压力/FP；上覆压力/OP；岩性/TYP 钻头参数 喷嘴等效直径/NS 
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表 2 因子分析结果
Table 2. Results of factor analysis
结果分类 分析参数 井深压力因子$ {F}_{1} $ 地震波速因子$ {F}_{2} $ 岩性因子$ {F}_{3} $ 贡献率 特征值 3.642 1.168 1.089 独立贡献率（%） 60.705 19.465 18.157 累积贡献率（%） 60.705 80.170 98.327 因子载荷矩阵 深度D 0.918 0.319 0.198 地震波速EV 0.326 0.929 0.178 孔隙压力PP 0.944 0.176 0.197 破裂压力FP 0.954 0.219 0.131 上覆压力OP 0.926 0.317 0.151 岩性TYP 0.189 0.156 0.969 因子得分矩阵 深度D 0.274 -0.088 -0.044 地震波速EV -0.305 1.209 -0.136 孔隙压力PP 0.300 -0.100 -0.052 破裂压力FP 0.339 -0.110 -0.039 上覆压力OP 0.292 -0.091 -0.037 岩性TYP -0.152 -0.154 1.087
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表 3 地质标签不同平面常数计算表
Table 3. Constants calculation table for different planes of geological labels
标签序号 常数Di 标签序号 常数Di 标签序号 常数Di 1 -0.542 0 5 1.348 2 9 3.231 9 2 -0.068 2 6 1.817 7 10 3.702 1 3 0.404 3 7 2.289 8 11 4.176 4 4 0.876 3 8 2.763 8 12 4.654 8
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