《石油地球物理勘探》：石油勘探技术研究双语文章推荐

石油地球物理勘探作为现代石油工业的关键技术领域，持续推动油气资源高效开发和发展。随着全球对油气资源需求的不断增长，以及勘探难度的逐步提升，地球物理勘探技术的创新与发展显得尤为重要。近年来，动态时间规整技术、时频电磁法、先验岩石物性约束反演、深度学习网络以及保真处理方法等前沿技术的引入，为石油地球物理勘探带来了新的突破和机遇。
本期精选文章聚焦于这些前沿技术在石油地球物理勘探中的应用与创新，深入探讨了多层位追踪方法、深层页岩气有利区预测、地球物理正则化反演、地震数据断层自动识别以及黄土山地三维地震资料处理等关键问题。接下来，让我们一同深入了解这些前沿研究成果，探索石油地球物理勘探的最新进展。

精选文章·Selected Articles

01

利用动态时间规整的多层位追踪方法

A multihorizon tracking method using dynamic time warping

【摘要】层位追踪是地震资料处理、解释中非常重要的步骤，现有的层位自动追踪技术在遇到断层时追踪效果不佳。为此，根据相邻地震道之间波形相似性，提出一种利用动态时间规整（DTW）的纯数据驱动的多层位追踪方法。首先，提取地震道特征值，将地震道按波谷、波峰或过零点等特征划分，使所追层位点严格遵循以上特征，保证追踪结果的高精度；其次，利用DTW方法计算两道相邻地震道划分好的特征值序列以得到相似路径；最后，从相似路径中提取所有彼此相似的特征值点对，并根据参考层划分特征值点对得到各套层位。模型数据试算和实际资料测试结果表明，所提方法能快速追踪到目标区域的各套层位，并有效克服断层对层位追踪的阻碍，对不同地质条件的地震资料具有一定的适用性，有一定的应用价值。

【Abstract】Horizon tracking is a very important step in seismic data processing and interpretation. The existing automatic horizon tracking technology often has a poor tracking effect when encountering faults. Therefore, a pure data-driven multihorizon tracking method using dynamic time warping (DTW) is proposed based on the waveform similarity between adjacent seismic channels. Firstly, the characteristic values of the seismic channels are extracted and the seismic channels are divided according to the characteristics of troughs, peaks, or zero crossings so that the tracked horizon positions strictly follow the above characteristics. In this way, a high accuracy of the tracking results can be ensured. Secondly, the DTW method is used to calculate the characteristic value sequences divided into two adjacent seismic channels to obtain similar paths. Finally, all the similar characteristic value point pairs, extracted from the similar paths, are divided according to the reference horizon to obtain each set of horizons. The results of model data calculation and actual data tests show that the proposed method can quickly track the positions of each set of horizons in the target area,and it effectively overcomes the hindering effect of faults on horizon tracking. It has a certain generalizability to seismic data in different geological conditions and has a certain application value.

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02

时频电磁法在深层页岩气有利区预测中的应用

Application of time-frequency electromagnetic method in predicting favorable areas for deep shale gas

【摘要】时频电磁法基于时—频域、电—磁场一体化探测理念，实现了多信息联合，弥补了传统电磁方法抗干扰能力不足的缺点，集成了可控源电磁法的优点：探测深度大，精度高，抗干扰能力强。在四川泸州地区开展时频电磁勘探，结合岩石物理和测井数据，对宝藏—云锦向斜的志留系五峰组—奥陶系龙马溪组页岩层系进行页岩气有利区预测。对本区外露头信息和电阻率测井数据进行统计，结果表明页岩含气性与电阻率具有相关性，高电阻率页岩段普遍表现出较高的含气性，本区具有开展电法勘探的物性基础。研究区不同地层之间存在明显的电性差异，纵向可划分为高、低相间的6套电性层，其中页岩气主力产层五峰—龙马溪组与上、下围岩电阻率差异明显。从时频电磁勘探原理出发，利用一维有限元和有限差分方法进行数值模拟，研究方法的可行性，并根据正演结果设计最佳采集参数。在围绕目的层进行针对性数据采集的基础上，采用自主研发的重、磁、电处理解释系统GeoGME进行数据处理解释，通过弱异常信息提取和井震双控约束反演等关键技术，探明了龙一1亚段各小层的电阻率和极化率分布特征。综合考虑目标页岩层段电阻率异常和极化率异常，预测出页岩气勘探有利区4个，为下一步该区域页岩气钻井部署提供了技术支撑，表明时频电磁法是进行深层页岩气有利区预测的有效勘探手段。

【Abstract】Based on the exploration principle of integrating time-frequency domain and electricmagnetic fields, time-frequency electromagnetic (TFEM) exploration compensates for the shortcomings of traditional electromagnetic methods in terms of insufficient anti-interference capability, and boasts advantages of controlled source electromagnetic methods such as multi-information integration and high precision. Guided by petrophysical and well logging data, we conduct a time-frequency electromagnetic data within the Silurian Wufeng Formation to Ordovician Longmaxi Formation shale series of the Baozang-Yunjin syncline in Luzhou to predict favorable areas for shale gas. Field outcrop measurements and resistivity logging data statistics indicate that high-resistivity shale formations generally exhibit better gas-bearing properties, providing the electric exploration with physical bases. Distinct electrical differences exist between different formations in the study area, which can be vertically divided into six alternating high-low resistivity layers. Notably, the Wufeng-Longmaxi formation, the primary shale gas production layer, exhibits significant resistivity differences from the host. Starting from the principles of time-frequency electromagnetic prospecting, we conduct numerical simulations using one-dimensional finite element and finite difference methods to validate the feasibility of the approach, and design optimal acquisition parameters based on the forward modeling results. After specifically collecting data on the targeted formation, we use the independently-developed system GeoGME to process and explain the data and clarify the distribution characteristics of the resistivity and polarization of small layers of Long 11 submember with the help of weak information extraction, well-seismic dual control constrained inversion, and other techniques. Comprehensively considering the resistivity anomalies and polarization anomalies of the targeted shale gas formation, we predict four favorable areas for shale gas prospecting, providing technical support for further deployment of shale gas drilling wells in this region. This study shows that the time-frequency electromagnetic method is effective for predicting favorable areas for deep shale gas.

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03

先验岩石物性约束的地球物理正则化反演

Geophysical regularization inversion constrained by priori petrophysical properties

【摘要】随着勘探程度的深入，可用于正则化反演的先验信息越来越丰富和精确。在分析参数变换函数、模糊C均值聚类模型约束、交替方向乘子优化等引入岩石先验物性约束方法的基础上，提出了一种基于反演单元物性互异原则的模型约束方法。基于单元互异原则的模型约束从地质单元数量有限、每个离散反演单元只能属于某一种岩性的本质出发，通过限定离散反演单元的物性取值实现物性引入。将上述先验物性引入与经典正则化反演相结合，构建了统一的目标函数并通过高斯—牛顿法进行优化求解；对四种方案实现岩石物性引入的作用机理和数学本质进行了分析，提出了同时利用多种方案提高反演效果的组合策略；对比了L1和L2范数最小结构模型约束与先验岩石物性引入策略结合的反演效果。模型和实测数据反演结果均表明，充分利用岩石物性测量的先验信息可有效提高反演效果。

【Abstract】As exploration deepens, the priori information available for regularization inversion becomes increasingly abundant and precise. A model constraint method is proposed based on the principle of mutual differences in the physical properties of inversion units, after an analysis of methods that introduce a priori rock physical property constraint, including parameter transformation functions, the fuzzy C-means (FCM) clustering model constraint and the alternating direction optimization of multipliers. The physical properties are introduced via the imposition of constraints on the values assigned to discrete inversion units, given that the essence of the model constraint based on the principle of mutual differences among inversion units is the finite number of geological units and that each discrete inversion unit can only belong to one lithology. A unified objective function is constructed through the combination of the aforementioned introduction of a priori physical properties with classical regularization inversion and is then optimized through the Gauss-Newton method. The mechanisms and mathematics essence underlying the introduction of rock physical properties through four distinct schemes are examined, and a strategy of employing multiple schemes to improve the inversion effect is proposed. Finally, the inversion effect of combining L1 norm minimum structure model constraints and the introduction strategy of a priori physical property constraints is compared with that of combining L2 norm minimum structure model constraints and the same strategy. The inversion results of the model and field data all demonstrate that leveraging a priori rock physical property information can effectively improve the inversion effect.

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04

基于AHRFaultSegNet深度学习网络的地震数据断层自动识别

Automatic fault recognition in seismic data based on AHRFaultSegNet deep learning network

【摘要】断层识别是地震数据解释的重要环节之一。深度学习技术的发展有效提高了断层自动识别的效率和准确性。然而，目前在断层的自动识别任务中，如何准确捕捉断层细微结构并有效抵抗噪声干扰仍然是一个具有挑战性的问题。为此，在HRNet网络的基础上，构建了一种基于解耦自注意力机制的高分辨率断层识别网络模型AHRFaultSegNet。对于自注意力机制解耦，结合空间注意力和通道注意力，代替HRNet中并行传播的卷积层，在减少传统自注意力机制计算量的同时，模型可以在全局范围内计算输入特征的相关性，更准确地建模非局部特征；对解耦自注意力使用残差连接来保留原始特征，在加速模型训练的同时，使模型能够更好地保持细节信息。实验结果表明，所提出的网络模型在Dice、Fmeasure、IoU、Precision、Recall等性能评价指标上均优于其他常见的断层自动识别网络模型。通过对合成地震数据与实际地震数据等进行测试，证明了该方法对断层细微结构具有良好的识别效果并且具有良好的抗噪能力。

【Abstract】Fault recognition is an essential step in seismic data interpretation. The development of deep learning has effectively improved the efficiency and accuracy of automatic fault recognition. However, in automatic fault recognition, it is still challenging to accurately capture subtle structures of faults and effectively resist noise interference. Thus, in this study, we propose a high-resolution fault recognition network model, AHRFaultSegNet, based on the HRNet network and decoupled self-attention mechanisms. The decoupling of self-attention mechanisms combines spatial attention and channel attention, replacing parallel convolution layers in HRNet.This reduces the computational amount of traditional self-attention mechanisms while allowing the model to calculate the relevance of input feature on a global scale, thus more accurately modeling non-local features. In decoupled self-attention, the residual connection is employed to preserve the original feature, speeding up model training and better maintaining detailed information. Experimental results demonstrate that the proposed network model outperforms other common automatic fault recognition network models in performance evaluation indexes such as Dice, Fmeasure, IoU, Precision, and Recall. Through fault recognition experiments on synthetic seismic data and actual seismic data, this method is proven to be effective in subtle fault structure identification and robust in noise resistance.

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05

提高黄土山地三维地震资料信噪比和分辨率的保真处理方法

Fidelity processing methods for improving signal-to-noise ratio and resolution of 3D seismic data in loess mountainous landforms

【摘要】黄土山地地表条件复杂、干扰强，表层介质非均质性强，同时受表层巨厚黄土吸收衰减影响，出现地震资料信噪比低、主频低、频带窄等问题。经叠前保真噪声衰减处理和叠前时间偏移后的叠加数据仍存在随机噪声及散射干扰，制约了薄储层的预测精度。业界通常采用F-XY域四维去噪+叠后零相位反褶积方法提高信噪比、分辨率，笔者则采用F-X域Cadzow滤波实现三维叠后数据的散射干扰及随机噪声同步压制，在此基础上利用连续小波变换方法提高分辨率。各处理环节中，应用噪声剖面、F-K谱、振幅谱、时间切片、分频扫描、井震标定等多种质控手段确保参数的合理选择。该套处理方法具有良好的保真性，可为后续反演、属性分析等环节提供良好的数据基础。

【Abstract】The surface condition of loess mountainous landforms is complex, the disturbance is strong, and the surface medium is heterogeneous. At the same time, due to the absorption attenuation of the surface thick loess, some problems have emerged in seismic data such as low signal-to-noise ratio, low main frequency, and narrow frequency band. After pre-stack fidelity noise attenuation processing, there are still random noise and scattering interference in the stack data after the pre-stack time migration, which restrict the precision accuracy of thin reservoirs. The proposed method in this paper breaks through the processing methods commonly employed in the industry to improve the signal-to-noise ratio and resolution by four-dimensional de-noising in the FXY domain and post-stack zero-phase de-convolution methods. In this paper, the method of Cadzow filtering in the FX domain is employed to realize the synchronous suppression of scattering interference and random noise of 3D post-stack data. On this basis, continuous wavelet transform is adopted to improve the resolution. Va-rious quality control methods are applied in each processing link to ensure the reasonable selection of para-meters, including noise profile, F-K spectrum, amplitude spectrum, time slicing, frequency division scanning, and well seismic calibration. The processing methods have good fidelity and can provide a good data basis for subsequent inversion and attribute analysis.

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期刊推荐·Recommend Journal

本刊面向国内外的石油勘探、地矿、煤田、计算机数字处理等的教学、科研、生产等行业和单位，及时传播物探技术信息，推广新技术、新经验，促进物探领域的科技进步。

主要报道（1）各种地球物理勘探方法（地震勘探、重磁勘探、电法勘探、井中地球物理测试）的新理论、新技术、新工艺和新经验；（2）各种地球物理勘探方法的应用新成果及典型实例；（3）地球物理数据处理新方法；（4）物探技术方面软件开发与应用；（5）地球物理的评述、讨论和论坛；（6）我国知名地球物理学家的生平事迹介绍；（7）国内外地球物理技术发展动态及学术活动。

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