Research and application of automatic adjustment method of stratigraphic model while drilling

QiFeng SUN, HuaMin GUO, XiZhou YUE, PengYun ZHANG, ChengLiang HU

Prog Geophy ›› 2025, Vol. 40 ›› Issue (5) : 1977-1986.

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Prog Geophy ›› 2025, Vol. 40 ›› Issue (5) : 1977-1986. DOI: 10.6038/pg2025II0395

Research and application of automatic adjustment method of stratigraphic model while drilling

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Abstract

In the process of horizontal well drilling, timely adjustment of the stratigraphic model based on Logging While Drilling (LWD) data is crucial for optimizing the drilling process and improving efficiency. In this paper, we propose an automatic adjustment method for the stratigraphic model while drilling. The method establishes an initial geological model based on pilot well logging data and extracts logging response characteristics between formations. During the drilling process, wavelet transform is used to segment the real-time logging response curves. The logging curves are reconstructed by integrating multiple types of information from time series, and then the Dynamic Time Warping(DTW) lower bound function and fastDTW algorithm based on early abandonment are applied to quickly search for the optimal matching segment within the constructed candidate sequence dataset, achieving formation comparison between the horizontal well and the pilot well. Finally, the stratigraphic model is adjusted based on the results of the formation comparison, thereby obtaining the true subsurface geological structure. The application results show that after adjustment using the method proposed in this paper, the morphological trend changes of the measured and simulated curves on the horizontal channel match closely, meeting the accuracy and real-time requirements for stratigraphic model adjustment while drilling.

Key words

Logging curve / Wavelet transform / Dynamic Time Warping(DTW) / Stratigraphic correlation / Stratigraphic model adjustment

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QiFeng SUN , HuaMin GUO , XiZhou YUE , et al . Research and application of automatic adjustment method of stratigraphic model while drilling[J]. Progress in Geophysics. 2025, 40(5): 1977-1986 https://doi.org/10.6038/pg2025II0395

References

Cao C W , Bo M . Well trajectory control technique by minimum curvature method. Oil Drilling & Production Technology, 2012, 34(3): 1- 6.
Ding L , Chen D Y , Hu X Y , et al. Optimization and application of fast dynamic time wrapping algorithm in logging curve similarity measurement. Journal of Jilin University (Earth Science Edition), 2022, 52(6): 2042- 2050.
Gao C Y , Zhou L F , Lu P . Review of the development of well log normalization. Progress in Geophysics, 2020, 35(5): 1777- 1783.
Geler Z, Kurbalija V, Ivanovi c ′ M, et al. 2019. Dynamic time warping: Itakura vs Sakoe-Chiba. //2019 IEEE International Symposium on INnovations in Intelligent SysTems and Applications (INISTA). Sofia: IEEE, 1-6, doi: 10.1109/INISTA.2019.8778300.
Gong F M , Chen T , Gong W J , et al. Application of string matching curve in contrast to stratigraphic correlation. Well Logging Technology, 2017, 41(1): 114- 119.
Itakura F . Minimum prediction residual principle applied to speech recognition. IEEE Transactions on Acoustics, Speech, and Signal Processing, 1975, 23(1): 67- 72.
Jin J C , Ma C Z , Chen G L , et al. Geomagnetic sequence positioning algorithm based on dynamic time warping of UCR strategy. Journal of Hefei University of Technology (Natural Science), 2021, 44(11): 1551- 1556.
Li G S , Song X Z , Tian S C . Intelligent drilling technology research status and development trends. Petroleum Drilling Techniques, 2020, 48(1): 1- 8.
Li H L , Liang Y , Wang S C . Review on dynamic time warping in time series data mining. Control and Decision, 2018, 33(8): 1345- 1353.
Li J C. 2020. Research on the stratigraphic correlation method of logging curve based on vortex search algorithm [Master's thesis](in Chinese). Daqing: Northeast Petroleum University, doi: 10.26995/d.cnki.gdqsc.2020.000732.
Li J R , Song W G . The minimum curvature algorithm of 3D well trajectory display. Journal of Hubei University of Technology, 2017, 32(1): 60- 62.
Quan J M . Research on comparison of LWD curve based on relative strata depth method. Well Logging Technology, 2016, 40(2): 180- 183.
Rakthanmanon T, Campana B, Mueen A, et al. 2012. Searching and mining trillions of time series subsequences under dynamic time warping. //Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Beijing: ACM, 262-270, doi: 10.1145/2339530.2339576.
Sakoe H , Chiba S . Dynamic programming algorithm optimization for spoken word recognition. IEEE Transactions on Acoustics, Speech, and Signal Processing, 1978, 26(1): 43- 49.
Shang F H , Ma N , Du R S . Similarity search of well-logging curve based on morphological characteristics. Application Research of Computers, 2013, 30(4): 1076- 1078. 1076-1078, 1081
Shen J Y. 2017. A novel similarity measure model for multivariate time series based on LMNN and DTW [Master's thesis](in Chinese). Hangzhou: Zhejiang University.
Sun L X , Han H W , Feng D Y , et al. Research status and outlook of logging stratigraphic division methods based on artificial intelligence. Petroleum Geology and Recovery Efficiency, 2023, 30(3): 49- 58.
Sun L X , Li Z R , Li K , et al. Cross-well lithology identification based on wavelet transform and adversarial learning. Energies, 2023, 16(3): 1475
Wang C , Long Y W , Yin W H , et al. Research on distance measurement method of improved DTW lower bound function. Computer Engineering and Applications, 2022, 58(23): 316- 326.
Wei S Y . Correlating method of the oil layers for the horizontal well in thin oil reservoirs. Petroleum Geology & Oilfield Development in Daqing, 2019, 38(3): 80- 86.
Xu H F , Feng R H , Zhang W K . C-DTW for human action recognition based on nanogenerator. Sensors, 2023, 23(16): 7230
Xue B , Yang Q , Zhang C H . Automatic stratification method of logging curve based on morphological filtering and wavelet transform. Progress in Geophysics, 2020, 35(1): 203- 210.
Zeng Y J , Wang M S , Guang X J , et al. Progress and prospects of Sinopec's intelligent drilling technologies. Petroleum Drilling Techniques, 2024, 52(5): 1- 9.
传文 , . 最小曲率法井眼轨迹控制技术研究与应用. 石油钻采工艺, 2012, 34(3): 1- 6.
, 殿远 , 向阳 , 等. 加速动态时间规整算法在测井曲线相似性度量中的改进及其应用. 吉林大学学报(地球科学版), 2022, 52(6): 2042- 2050.
春云 , 立发 , . 测井曲线标准化研究进展综述. 地球物理学进展, 2020, 35(5): 1777- 1783.
法明 , , 文娟 , 等. 字符串动态匹配算法在地层对比中的应用. 测井技术, 2017, 41(1): 114- 119.
俊超 , 昌忠 , 国良 , 等. 基于UCR-DTW的地磁序列定位算法. 合肥工业大学学报(自然科学版), 2021, 44(11): 1551- 1556.
根生 , 先知 , 守嶒 . 智能钻井技术研究现状及发展趋势. 石油钻探技术, 2020, 48(1): 1- 8.
海林 , , 少春 . 时间序列数据挖掘中的动态时间弯曲研究综述. 控制与决策, 2018, 33(8): 1345- 1353.
建蓉 , 文广 . 三维轨迹显示最小曲率算法研究. 湖北工业大学学报, 2017, 32(1): 60- 62.
李金成. 2020. 基于涡流优化算法的测井曲线地层对比方法研究[硕士论文]. 大庆: 东北石油大学, doi: 10.26995/d.cnki.gdqsc.2020.000732.
景明 . 基于RSD方法随钻测井曲线实时对比技术研究. 测井技术, 2016, 40(2): 180- 183.
福华 , , 睿山 . 基于形态特征的测井曲线相似性搜索研究. 计算机应用研究, 2013, 30(4): 1076- 1078. 1076-1078, 1081
沈静逸. 2017. 基于DTW和LMNN的多维时间序列相似性分析方法[硕士论文]. 杭州: 浙江大学.
龙祥 , 宏伟 , 德永 , 等. 基于人工智能的测井地层划分方法研究现状与展望. 油气地质与采收率, 2023, 30(3): 49- 58.
, 英文 , 炜宏 , 等. 改进DTW下界函数的距离度量方法研究. 计算机工程与应用, 2022, 58(23): 316- 326.
淑燕 . 薄油层水平井油层对比方法. 大庆石油地质与开发, 2019, 38(3): 80- 86.
, , 超虹 . 基于形态学滤波与小波变换的测井曲线自动分层方法. 地球物理学进展, 2020, 35(1): 203- 210.
义金 , 敏生 , 新军 , 等. 中国石化智能钻井技术进展与展望. 石油钻探技术, 2024, 52(5): 1- 9.

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