考虑异常压力的碳酸盐岩钻前孔隙压力预测新模型

0 ENERGY & FUELS
Xinyu Guo , Ming Tang , Shiming He , Lu Zou , Guangfu Zhang , Long Zhang , Yu Zhang
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引用次数: 0

摘要

碎屑岩孔隙压力预测方法已经建立,精度较高,但不能直接应用于碳酸盐岩地层。现有碳酸盐岩孔隙压力预测模型未能充分考虑成岩过程异常高压的作用机制,适应性差,误差较大。这就导致了泥浆密度设计的缺陷和频繁的钻井问题,如泄漏和溢流。本文提出了一种综合碳酸盐岩成岩作用增压与降压机制的一维孔隙压力预测新方法。此外,利用井震相关性,建立了基于序贯高斯共克里格插值的三维孔隙压力预测模型。该模型考虑了缝洞系统的影响,可以更准确地估计钻前孔隙压力。结果表明,新的一维预测方法与实测孔隙压力值非常吻合,误差范围为- 7.35% ~ 5.87%。序贯高斯共克里格插值方法通过平衡断裂断裂带的随机性和非断裂断裂带的连续性,克服了单一插值方法的局限性。三维孔隙压力模型的钻前预测结果与数值结果非常吻合,误差在±10%以内。该方法考虑了异常压力的形成机制,提高了碳酸盐岩孔隙压力预测的准确性,支持了有效的风险评估和复杂钻井条件分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A new pore pressure model for pre-drilling prediction in carbonate rocks considering the abnormal pressure
The pore pressure prediction methods for clastic rocks are well-established and highly accurate but are not directly applicable to carbonate formations. Existing carbonate pore pressure prediction models fail to fully account for the mechanisms of abnormal high pressure during diagenesis, leading to poor adaptability and significant errors. This results in flawed mud density designs and frequent drilling issues such as leakage and overflow. This study proposes a new one-dimensional pore pressure prediction method that incorporates both pressurization and depressurization mechanisms in carbonate diagenesis. Additionally, using well-seismic correlation, a three-dimensional pore pressure prediction model is developed based on sequential gaussian co-kriging interpolation. This model accounts for the influence of fracture-cavity systems, enabling more accurate pre-drilling pore pressure estimation. The results demonstrate that the new one-dimensional prediction method closely aligns with measured pore pressure values, with an error range of −7.35 %∼ 5.87 %. The sequential gaussian co-kriging interpolation overcomes the limitations of single interpolation methods by balancing the randomness of fractured fault zones with the continuity of non-fractured regions. The 3D pore pressure model's pre-drilling predictions show strong agreement with numerical results, with errors within ±10 %. By considering the formation mechanisms of abnormal pressure, this approach enhances the accuracy of carbonate pore pressure predictions, supporting effective risk assessment and the analysis of complex drilling conditions.
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