基于“四元致险”模型的地震导向钻井地质漏失风险层预测方法

doi:10.3969/j.issn.2096-1693.2025.01.016

摘要/Abstract

摘要：

钻井漏失作为钻井工程中最常见的复杂与事故类型之一，其精准预测对保障油气资源的安全高效勘探开发具有重要意义。然而，传统漏失风险预测方法依赖历史钻测井数据与经验分析，欠缺对地质构造特征等关键地质风险要素的考虑，存在预测滞后性与空间局限性，难以满足复杂地层钻前预测需求。针对上述问题，本文提出基于“四元致险”模型的地震导向钻井地质漏失风险预测方法。基于海上钻井典型区块的跨尺度数据，融合测井、钻井与三维地震信息，从地质统计与典型井分析入手，系统揭示了断裂带、火山通道、岩性突变界面与异常高压地层4类主控致险因素，构建了“四元致险”模型框架。进一步以地震信息为主导，融合测井与钻井数据的约束机制，提取多源敏感地震属性，建立四类风险体的识别方法，即通过多属性贝叶斯融合建立断裂带风险概率模型，振幅-方差联合分析识别火山通道边界，响应特征优选构建岩性界面敏感属性集，结合孔隙压力反演实现异常高压层预测。渤海A区和南海B区的实际应用表明，多口钻井钻前漏失风险预测与实际钻井过程中的风险事故吻合率较高，其中成功预测渤海H1井80%漏失层位，包括多个复合成因的漏失层，瞬时漏速达90 m³/h，验证了该模型对复杂地层钻井风险的前瞻有效预测能力。总之，研究成果构建了一套面向复杂构造区的地震导向的三维钻前漏失地质风险综合识别流程，为井位部署、轨迹设计与钻井安全管理提供关键支撑。

关键词: 钻井漏失, 地震导向钻井, 四元致险模型, 地震属性, 钻前预测, 地质体识别

Abstract:

Lost circulation is one of the most frequent and hazardous complications in drilling operations, and its accurate prediction plays a vital role in ensuring the safe and efficient exploration and development of hydrocarbon resources. However, conventional prediction methods largely rely on historical drilling and logging data combined with empirical analyses, while often neglecting critical geological risk elements such as structural features. These methods suffer from delayed predictions and limited spatial applicability, making them insufficient for pre-drilling risk assessment in complex geological environments. To address these challenges, this study proposes a seismic-guided prediction method for geological lost circulation risks based on a “four-element hazard” (FEH) model. Utilizing multi-scale data from representative offshore drilling blocks, the method integrates well-logging data, drilling parameters, and 3D seismic information. Through geological statistics and analysis of typical well sections, four major geological factors are identified as the primary triggers for lost circulation: fault zones, volcanic conduits, lithologic discontinuities, and abnormally overpressured formations. These factors form the foundation of the FEH model framework. Guided primarily by seismic data and constrained by well and drilling information, the method extracts multi-source sensitive seismic attributes to establish identification workflows for each of the four risk types. Specifically, a multi-attribute Bayesian fusion model is used to estimate fault-related risk probabilities; joint amplitude-variance analysis delineates the boundaries of volcanic conduits; lithologic interface indicators are optimized based on response features; and abnormal overpressure zones are predicted by integrating seismic velocity and pore pressure inversion. Field applications in the Bohai A Block and South China Sea B Block demonstrate strong consistency between predicted risk zones and actual lost circulation events. In particular, the model successfully forecasted 80% of the loss intervals in the Bohai H1 well, including several composite-origin zones, with a maximum instantaneous loss rate of 90 m³/h. These results validate the model’s capability for forward-looking and effective risk prediction in structurally complex formations. In summary, this research develops a three-dimensional, seismic-guided, pre-drilling risk identification workflow targeting structurally complex zones. The method provides essential technical support for well placement optimization, trajectory design, and proactive drilling risk management.

Key words: lost circulation, seismic-guided drilling, four-element hazard model, seismic attributes, pre-drilling prediction, geological body identification

中图分类号:

陈帅, 袁三一, 袁俊亮, 丁智强, 许言午. 基于“四元致险”模型的地震导向钻井地质漏失风险层预测方法[J]. 石油科学通报, 2025, 10(3): 478-495.

CHEN Shuai, YUAN Sanyi, YUAN Junliang, DING Zhiqiang, XU Yanwu. Seismic-guided prediction of geological lost circulation risk zones based on a “four-element hazard” model[J]. Petroleum Science Bulletin, 2025, 10(3): 478-495.

https://sykxtb.cup.edu.cn/CN/Y2025/V10/I3/478

图/表 19

图1 渤海A研究区地层综合柱状简图

Fig. 1 Integrated stratigraphic column of the Bohai A study area

图2 各类致险因素相关漏失点的统计分布图

Fig. 2 Statistical distribution of lost circulation points associated with different risk factors

图3 W1井漏失点处断裂特征

Fig. 3 Fracture characteristics at lost circulation points of Well W1

图4 W1井漏失点电成像测井响应及裂缝发育特征示意图

Fig. 4 Electrical imaging logging response and schematic of fracture development at the lost circulation point of Well W1

图5 火山通道的典型地震响应特征

Fig. 5 Typical seismic response characteristics of a volcanic conduit

图6 典型火山通道结构示意图

Fig. 6 Schematic diagram of a typical volcanic conduit structure

图7 W3井厚泥夹砂漏失层段的综合录井图

Fig. 7 Comprehensive mud logging chart of the lost circulation interval in thick mudstone interbedded with sandstone in Well W3

图8 W4井岩性界面漏失层段的综合录井图

Fig. 8 Comprehensive mud logging chart of the lithologic interface-related lost circulation interval in Well W4

图9 厚泥夹薄砂层段应力-应变与井漏关系图(改编自邓津辉等^[44])

Fig. 9 Relationship diagram between stress-strain and well leakage in thick mudstone interbedded with thin sandstone (modified from Deng et al^[44])

图10 W5井异常高压致漏层段的综合录井图

Fig. 10 Comprehensive mud logging chart of the lost circulation interval induced by abnormal overpressure in Well W5

图11 渤海A工区多种地震属性体 (a) 原始振幅属性；(b) 最大振幅属性；(c) 均方根振幅属性；(d) 反射强度属性；(e) 相对波阻抗属性；(f) 蚂蚁体属性；(g) 方差属性；(h) 倾角属性

Fig. 11 Multiple seismic attribute volumes in the Bohai A block (a) original amplitude attribute (b) maximum amplitude attribute (c) root mean square amplitude attribute (d) reflection strength attribute (e) relative acoustic impedance attribute; (f) ant-tracking attribute; (g) variance attribute; (h) dip angle attribute

图12 岩性界面敏感属性优选图

Fig. 12 Sensitive attribute selection for lithologic interfaces

图13 W6井周多属性断裂风险识别结果

Fig. 13 Results of multi-attribute fracture risk identification around well W6

图14 W7和W8井周火山通道风险识别图

Fig. 14 Volcanic conduit risk identification around wells W7 and W8

图15 W9井岩性界面风险识别图

Fig. 15 Lithologic interface risk identification around Well W9

图16 W10井异常高压地层风险识别图

Fig. 16 Abnormal overpressure risk identification in Well W10

图17 H1井综合地质漏失风险层预测

Fig. 17 Integrated prediction of lost circulation risk zones in Well H1

表1 H1井综合地质漏失风险层预测表

Table 1 Integrated prediction of lost circulation risk zones in Well H1

风险层	深度/m	预测主因
1	642~668	断裂
2	1256~1286	断裂+岩性界面
3	2987~3090	断裂+岩性界面
4	3204~3252	断裂
5	3462~3535	断裂+岩性界面
6	3576~3618	断裂
7	4368~4407	岩性界面+异常高压

表2 H1井漏失实钻记录

Table 2 Actual lost circulation events in Well H1

漏失点	深度/m	瞬时漏速/(m³/h)	预测结果
1	3044	60	正确
2	3055	30	正确
3	3065	90	正确
4	3214	80	正确
5	3407	6	遗漏
6	3482	30	正确
7	3529	6	正确
8	3602	6	正确
9	3644	5	遗漏
10	4389	15.6	正确

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