考虑方向和非线性增强的断裂定量识别模型

A quantitative fracture identification model considering orientation and nonlinear enhancement

摘要

断裂发育的深部油气资源逐渐成为能源勘探和开采的重点区域,用于识别深部断裂的地震波在深层、超深层中传播的复杂性和衰减性,导致地震成像结果模糊、分辨率低。同时,目前多数商业地震解释软件在深层复杂构造识别方面存在处理流程固定、识别精度有限等局限。针对这些问题,提出一种用MATLAB代码编程实现的深部储层断裂识别方法,基本流程为:首先,对原始三维地震数据进行高斯滤波平滑;再提取各向异性特征定义相干属性;接着通过三维Laplacian卷积提取边缘响应,并融合相干和拉普拉斯响应属性值;随后增强水平梯度幅值,同时通过指数衰减抑制垂向梯度干扰;最后进行归一化操作并基于Sigmoid函数非线性增强对比度生成断裂识别体。公式推导和数据测试均证明了结构张量各向异性特征与方向增强融合方法的可行性。结果表明,相较于传统三维地震断裂识别方法,所提出的方法具有更好的抗噪声干扰能力和复杂断裂特征分辨能力。

Abstract

Deep and ultra-deep fractured reservoirs are important targets for future energy exploration and development. However, the complexity and attenuation of seismic wave propagation in deep formations often result in blurred images and low resolution. In addition, most commercial interpretation software has limitations in identifying deep complex structures because of fixed processing workflows and insufficient detail control. To address these challenges, this study proposes a MATLAB-based method for refined fracture identification in deep reservoirs. The proposed workflow includes the following steps. First, Gaussian filtering is applied to smooth the raw 3D seismic data. Second, anisotropic characteristics are extracted to calculate coherence attributes. Third, edge responses are obtained using 3D Laplacian convolution, and the coherence and Laplacian response attributes are integrated. Subsequently, the horizontal gradient amplitudes are enhanced while vertical gradient interference is suppressed through an exponential decay function. Finally, normalization and nonlinear contrast enhancement based on the Sigmoid function are performed to generate a refined fracture identification volume. Formula derivation and data validation confirm the feasibility of the structural tensor-based anisotropy extraction and directional enhancement fusion method. Application results demonstrate that the proposed method exhibits stronger noise resistance and provides higher-resolution imaging of complex fracture systems compared with traditional 3D seismic fracture identification methods.

关键词

深部地层 / 断裂识别 / 结构张量 / 边缘检测 / 地震数据

Key words

deep formation / fracture identification / structure tensor / edge detection / seismic data

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基金资助

国家自然科学基金面上项目(52374021)

企业创新发展联合基金重点支持项目(U24B2029)