Based on the combination ofdata-and model-driven approaches,this study expanded the labels of the training set through model inversion results,and added the model inversion objective function to the deep learning algorithm.By constructing a new loss function,this study proposed a seismic impedance optimization inversion method combining model inversion with deep learning inver-sion.The semi-supervised deep learning network inversion under a pseudo-label was achieved using the RNN network structure.The network inversion results were used as the initial model to participate in the model inversion.The final optimization inversion was com-pleted by continuous iterative optimization of both network and model inversion.The method proposed in this study proves to possess high inversion accuracy and practicability,as demonstrated by the synthesis of the Marmousi model and the actual data.

Abstract The application of deep learning methods for seismic impedance inversion usually requires a large amount of labeled data to train the network, while labeled data available in practical applications is often limited, which affects the effectiveness of the relevant methods. In order to address this problem, this paper proposes one kind of deep learning method of a closed-loop cycle Wasserstein generative adversarial network (Cycle-WGAN) for seismic impedance inversion based on the combination of “data-driven and model-driven”. The method uses a small amount of labeled data and unlabeled seismic data generated by the forward modeling. It constitutes a bidirectional cycle of inversion and forward modeling through the generative and adversary networks for the inversion and generative and adversary networks for the forward modeling by convolution model, which improves the conventional GAN networks. The proposed method also introduces the Wasserstein loss function to improve the neural network’s training stability. Tested on the Marmousi model with complex structure, the proposed Cycle-WGAN network can effectively obtain the seismic impedance inversion results. Moreover, it is highly robust when seismic data are noisy and has higher accuracy than the inversion results from some conventional neural networks, such as RNN (Recurrent Neural Network), TCN (Temporal Convolutional Network, WGAN (Wasserstein Generative Adversarial Network), etc.

It is of great significance to reduce the uncertainty of seismic phase analysis results by combining multiple deep learning algorithms to mine hidden and useful information in seismic data,and to achieve mutual complementarity and optimization.Therefore,a method and process of deep learning seismic phase analysis from label training to data mining to optimization were proposed.Firstly,waveform classification is per-formed by the SOM of the self-organizing mapping network diagram,which provides representative training data for supervised learning.Then,the convolutional neural network CNN and the circulating neural network RNN are used for seismic phase analysis,and the predicted seismic phase analysis results are input to the generative adversarial neural network GAN for optimization between algorithms and uncertainty analysis of operation results,and finally the optimal results are given based on actual data analysis.The method and practical process of SOM+CNN/RNN+GAN combined supervised and unsupervised deep learning seismic facies analysis are proposed and realized,and it is proved that the method improves the reliability and effect of seismic facies analysis and oil and gas reservoir prediction results through the practical application of oil and gas prediction in river channel sand reservoir reservoirs in the study area.

To analyze seismic wave field characteristics and characterize fracture (or crack) reservoirs, it is essential to build proper wave-induced fluid flow (WIFF) models of various scales. There is much research related to WIFF fractured models that are mainly suitable only for different scales of fracture (crack) medium separately, such as microscopic cracks and mesoscopic fractures. Based on previous research, it is proposed a unified multiscale (mesoscopic and microscopic) dispersion and attenuation model for the medium with fractures, cracks, pores, and fluid. The formulation uses frequency-dependent fractured (or crack) parameters expressed as the form of multiplication of fracture parameters and relaxation function. The advantage of this method is that it is convenient to build fluid porous medium with different scale fractures (or cracks) and various fracture (or crack) configurations. The numerical simulation results prove the correctness and applicability of the proposed extended WIFF dispersion and attenuation model. Based on our proposed method, the characteristics of the dispersion and attenuation of the multiscale fractured model are analyzed. The results indicate that the characteristics of velocity dispersion and wave attenuation in the medium with different scales of fractures are similar. The velocity increases with frequency and finally tends to be stable. The main difference among the different scales of models is that the frequency bands of the dispersion and attenuation occurring are different. We also discover that for multiscale fractured medium, the characteristic frequency and attenuation peaks do not necessarily correspond to each other, which makes the analysis of the dispersion and attenuation more complicated.

地下储层中存在介观尺度的裂缝是导致地震波的速度频散和能量衰减的一个重要原因.从 Galvin介观裂缝模型出发,重构其低频极限和高频极限的表达形式,将频散关系施加到裂缝模型上构建依赖频率的裂缝柔度参数,建立了一种改进的介观尺度的裂缝型岩石物理模型.基于该改进模型,利用附加柔度的组合性质,可以容易地构建更复杂的模型并进行依赖频率的地震响应特征分析.在传统的反射系数公式中引入频率参数,分析了具有不同裂缝长度、背景渗透率、流体粘度等频散敏感参数的反射界面上的频散 AVO 及地震记录响应特征.通过数值模拟得出频散敏感参数主要影响发生频散的频段,即影响岩石的特征频率;当模型的特征频率与地震波频段主频相近时,频散现象最突出,当特征频率大于地震波频段主频一个数量级时,可以忽略频散作用,此时采用传统的 Gassmann方程即可较准确地分析地震剖面的特征.基于改进模型得到的认识为地震频散特征的实际应用提供了岩石物理模型的构建方面的指导.

基于属性建模的数值模拟方法正在成为复杂地震响应特征分析的一种有力手段,这里在二维数值模拟方法研究中,提出和采用了基于多种信息的属性建模方法,包括将机器学习算法应用到属性建模中,利用U-net网络改进了低信噪比资料的断缝系统识别精度,并将这种识别结果用于潜山内幕复杂断缝系统的建模中,再通过有限差分数值模拟方法,得到了较为符合地下实际条件的地震响应特征数值模拟结果,并且与实际资料上的复杂波场特征对应度高,实现了几何和物理参数的空间变化模拟,提高了数值模拟的精度和可靠度.应用提出的属性建模地震响应特征分析方法及流程,证实了研究区潜山内幕断缝系统的地震响应特征主要呈现为"高陡网状反射"和"短轴不连续反射"的特征及相关结论,为研究区复杂潜山储层地震响应特征认识和裂缝预测提供了借鉴.

宽方位地震资料波场正演响应特征表明:地震纵波在地下地质体中传播时,反射系数在不同的方向具有明显的方位各向异性特征.利用方位各向异性进行裂缝预测已经成为国内外的研究热点之一.本文通过地震纵波随方位变化的正演响应特征分析,结合Bakulin等提出的含流体裂缝各向异性参数之间的相互关系,对Rüger公式进行了近似简化,推导了裂缝型储层含流体情况下,可以用于表征裂缝发育的各向异性参数γ与反射系数之间的表达式,提出了一种基于各向异性参数反演的裂缝预测方法.通过理论模型和实际资料应用证明了方法的有效性和适用性,为应用宽方位叠前地震资料进行裂缝预测提供了一种可行的方法技术.

PreviousNext No AccessSEG 2021 Workshop: 4th International Workshop on Mathematical Geophysics: Traditional & Learning, Virtual, 17–19 December 2021Iterative optimization of labeled data in CNN algorithm and its application to small faults identificationAuthors: Wenlu HuangJianguo YanHui LiWenlu HuangChengdu University of TechnologySearch for more papers by this author, Jianguo YanChengdu University of TechnologySearch for more papers by this author, and Hui LiChengdu University of TechnologySearch for more papers by this authorhttps://doi.org/10.1190/iwmg2021-16.1 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract The representativeness and universality of labeled data is one of the important factors affecting the accuracy and generalization of CNN algorithm. At present, most fault identification methods in CNN-based algorithm use the theoretical labeled data. This paper proposes a method for iterative optimization of theoretical labeled data and field labeled data to obtain the final labeled data, which has good representativeness due to field seismic data based and good universality due to synthetic data based. The CNN model trained on the final labeled data has better generalization. The method was applied to identifying the small faults and fracture joint system in the deep buried hill reservoirs in Bohai Bay, where the seismic data appears low signal-to-noise ratio (SNR). The good results have been achieved, which proves the effectiveness and applicability of the method. Keywords: optimization, neural networks, machine learning, deconvolution, algorithmPermalink: https://doi.org/10.1190/iwmg2021-16.1FiguresReferencesRelatedDetails SEG 2021 Workshop: 4th International Workshop on Mathematical Geophysics: Traditional & Learning, Virtual, 17–19 December 2021ISSN (online):2159-6832Copyright: 2022 Pages: 193 publication data© 2022 Published in electronic format with permission by the Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished: 24 Feb 2022 CITATION INFORMATION Wenlu Huang, Jianguo Yan, and Hui Li, (2022), "Iterative optimization of labeled data in CNN algorithm and its application to small faults identification," SEG Global Meeting Abstracts : 61-64. https://doi.org/10.1190/iwmg2021-16.1 Plain-Language Summary Keywordsoptimizationneural networksmachine learningdeconvolutionalgorithmPDF DownloadLoading ...

The mechanism of dispersion and attenuation induced by fluid flow among pores and microcracks in rocks is an important research topic in geophysical domain. A generalised frequency-dependent fourth-rank tensor is proposed and derived herein by combining Sayers's discontinuity tensor formula and Gurevich's squirt flow model. Furthermore, a proposed method for establishing a cracked model with cracks embedded in a transversely isotropic (TI) background medium is developed. Based on the new formulation, we investigate the characteristics of dispersion, attenuation and azimuthal anisotropy of three commonly encountered vertical crack distributions, including aligned cracks, monoclinic cracks and cracks with partial random orientations. We validate the developed model by comparing its predictions with those of the classic anisotropic squirt flow model for an aligned crack. The numerical analyses indicate that the azimuth is independent of frequency when the maximum attenuation is observed for all three crack distributions. In a low-frequency range in the case of an anisotropic background, the attenuation of the qP-wave is inversely proportional to velocity, whereas the attenuation of the qSV-wave is proportional to velocity. In addition, the inherent anisotropy of the rock does not significantly affect the dispersion and attenuation owing to squirt flow. Finally, to investigate the applicability of the theory, we model laboratory data of a synthetic porous sandstone with aligned cracks. Overall, the models agree well with laboratory data. The complex characteristics determined through this study may be useful for the seismic characterisation of fractured reservoirs.

地震属性及地震反演结果中页岩油藏中的"甜点"会出现异常特征不明显的现象,这使得"甜点"预测成为一大难点.准噶尔盆地玛湖凹陷二叠系风城组风二段"甜点"层地震振幅较弱且连续性不好,属性分析和地震反演结果与地质评钻井结果不一致,给地震预测及井位选择等带来了的不确定性.为此,采用了基于属性建模的地震正、反演联合的方法对风二段"甜点"层地震响应特征的不确定性进行了分析.首先将反演得到的波阻抗与测井资料及实际地震剖面进行对比分析,重新计算几何和物性参数,建立用于正演模拟的几何和物性模型;然后利用波动方程数值模拟方法进行"甜点"地震响应特征的正演模拟计算;再将正演剖面与实际地震剖面和已钻井资料相结合,综合分析页岩油藏"甜点"地震响应特征及可能的变化规律,对地震预测的不确定性进行分析评估;最后将上述结论作为参考再次进行属性分析,给出重新预测的结果.研究区风二段"甜点"层地震响应特征不确定性分析为M AY1井的井位选择提供了充分的依据.研究结果表明,地震响应特征不确定性分析方法作为页岩油藏"甜点"预测的技术手段,能够较为准确地判断页岩油藏"甜点"地震响应特征,确立识别参数.

地震波场的方位特征对于裂缝性油气藏的地震预测方法研究有着重要的意义.为使裂缝模型更具一般性,本文基于线性滑动理论和Bond变换构造了两组任意夹角竖直裂缝模型;考虑到波场二维模拟中突出方位特征,依据弹性动力学的基本方程和Bond变换,推导出了含方位角的弹性波传播速度应力方程;使用高精度交错网格有限差分法对几种裂缝介质进行了数值模拟,并分析其波场特征的变化.模拟结果表明,在两组参数相同的任意夹角竖直裂缝模型中,裂缝内夹角各个方位的波场特征变化不明显,各向异性强度较低,裂缝外夹角各个方位的波场特征变化剧烈,裂缝正交时,各处波场特征相近;针对单组裂缝模型,分析了裂缝参数变化对波场特征的影响,总结出了三种波场形态,得出了裂缝垂直面的波场特征与裂缝法向弱度和切向弱度的相对大小有关,从裂缝垂直面到裂缝平行面的波场朝着相同的形态变化,与裂缝参数无关等认识.这些分析结果有助于进一步认识和应用裂缝介质的波场方位特征.

反Q滤波是提高地震资料分辨率和保幅处理的常用方法之一,在地震储层预测中具有重要的实用价值.长期以来人们不断加以研究改进,其中采用时变增益限振幅补偿函数的反Q滤波方法是当前研究改进的方向之一.本文通过对几种常用的反Q滤波方法进行研究,提出了一种基于Teager-Kaiser能量原理求取振幅补偿函数增益限的时变增益限反Q滤波方法,改进了传统反Q滤波方法中存在的不足.新方法基于平滑连续函数而不是基于常用反Q滤波方法中采用的分段函数或截止频率来计算补偿函数的时变增益极限,因此新方法具有稳定调整时变增益极限的优点,从而提高了反Q滤波的可靠性和精度,特别是对于深层介质的保幅及分辨率提高效果较好.本文用理论模型及实际资料证明了新方法的有效性及实用性.

近年来,在"提质增效,高效勘探"的总体战略背景下,地震勘探的评价优化引起了人们广泛关注.准噶尔盆地地震勘探资料的处理和解释工作中,通过实施面向目标的一体化工作流程,提出了"三单一策"的研究方法及评价体系,并在实际应用中取得了显著效果.但该评价体系没有包含地震资料的采集工作,并且主要采用的是一些定性描述方法.为此,通过构建以地震资料有效频宽为核心评价指标,提出了地震采集的相应指标体系,从而将地震采集方案评估及优化纳入到地震勘探的评价优化中,提出了"三单一策2.0",构建了一种地震勘探评价优化体系,并在多个勘探项目中实施,取得了显著的效果.所提出的方法思路,可为类似地区地震勘探的评价优化提供一定借鉴.

潜山已成为中国海域油气勘探的一个重要领域,并且向大于3500m的深埋潜山拓展.渤中19-6单层太古宇变质岩潜山大气田发现之后,多层结构的潜山成藏潜力大小成为急需解决的瓶颈.通过钻井、地震资料和地球化学数据,开展区域地质构造演化研究及成藏条件分析,结果表明:基于成山成储受控于区域构造活动及其相关的裂缝作用的认识,获得了渤中13-2油气田勘探发现(探明地质储量亿吨级油气当量),证实多层结构潜山的太古宇变质花岗岩具有极好的成藏条件;通过进一步对渤中13-2油气田的成藏要素分析及其与渤中19-6大气田的对比表明,多期立体网状裂缝及其与供烃窗口的连通性是潜山成储—成藏的关键,与断裂伴生的“短轴状不连续反射”可以作为太古宇潜山优质储层的识别标志;超压宽窗供烃—多元联合输导驱动了双层结构潜山成藏,网状连通的孔—缝体系为油气在潜山内部的运移聚集提供了有效空间.渤中13-2双层结构潜山油气发现,再次证实了裂缝为主导的非沉积岩潜山勘探思路,对中国海域潜山勘探具有重要的指导意义.

PreviousNext No AccessSEG 2020 Workshop: Broadband and Wide-azimuth Deepwater Seismic Technology, Beijing, China, 13–15 July 2020A new time-varying gain limits inverse Q filtering and its application to a study in Bohai BayAuthors: Yan JianguoSong XinleiChen QiDeng RubinZhang XuechunYan JianguoThe College of Geophysics, Chengdu University of Technology, ChinaSearch for more papers by this author, Song XinleiThe College of Geophysics, Chengdu University of Technology, ChinaSearch for more papers by this author, Chen QiThe College of Geophysics, Chengdu University of Technology, ChinaSearch for more papers by this author, Deng RubinThe College of Geophysics, Chengdu University of Technology, ChinaSearch for more papers by this author, and Zhang XuechunThe College of Geophysics, Chengdu University of Technology, ChinaSearch for more papers by this authorhttps://doi.org/10.1190/bwds2020_27.1 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract Inverse Q filtering of seismic data has become a common and useful approach in seismic reservoir characterization for increasing the resolution and preserving the amplitude of seismic data. We proposed a new time-varying gain limits inverse Q filtering with the continuous compensation functions instead of using the piecewise function or cut-off frequency to increase the quality of seismic amplitude compensation for reservoir characterization. By deriving a new relationship between the gain limits and formation quality factor Q, the stabilization factor and gain limits of compensation functions are time-varying. Basically, the gain of the compensation function in proposed method will increase when the attenuation and dispersion of seismic wave are strong in the subsurface, such as in the deep layer. So some significant improvements of quality of the inverse Q filtering are made by using this new approach. Theoretical and field examples have proved the validation of the method proposed, and the results are very encouraging when the method is applied to not only poststack data but also pre-stack data in the buried-hill basement rock reservoir characterization in the study area of Bohai Bay, in Eastern China. Keywords: Q, filtering, amplitude, seismic attributes, attenuationPermalink: https://doi.org/10.1190/bwds2020_27.1FiguresReferencesRelatedDetails SEG 2020 Workshop: Broadband and Wide-azimuth Deepwater Seismic Technology, Beijing, China, 13–15 July 2020ISSN (online):2159-6832Copyright: 2020 Pages: 155 publication data© 2020 Published in electronic format with permission by the Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished Online: 09 Nov 2020 CITATION INFORMATION Yan Jianguo, Song Xinlei, Chen Qi, Deng Rubin, and Zhang Xuechun, (2020), "A new time-varying gain limits inverse Q filtering and its application to a study in Bohai Bay," SEG Global Meeting Abstracts : 100-103. https://doi.org/10.1190/bwds2020_27.1 Plain-Language Summary KeywordsQfilteringamplitudeseismic attributesattenuationPDF DownloadLoading ...

为提高渤海M油田小尺度火成岩的成像质量,对基于单程波理论的多次波偏移方法进行研究.多次波偏移方法采用地震波场一次波与多次波的全波场信息,利用单程波理论对多次波进行互相关成像,能够提高火成岩的照明度及成像分辨率,同时提高了计算效率.由火成岩模型测试及实际数据应用证明,该方法能够改善火山通道的成像质量,提高小尺度火成岩的信噪比和分辨率,使火成岩同相轴刻画得更为清晰.利用该成像结果进行精细地震资料解释能够大幅度提高解释精度.

地震波传播速度参数贯穿于地震数据采集、处理和解释的整个过程.在地震资料处理中,速度分析是整个资料处理流程不可缺少的重要环节之一,通过速度分析得到一个正确的地震速度场,对于静(动)校正,以及叠加偏移等处理结果都有重要的影响,因此速度分析结果的精确与否直接影响地震成像的准确性.由于地下地质条件的复杂性,地震速度分析是一个反复迭代的过程,主要应考虑的影响因素包括:资料噪音、速度谱拾取密度、基于实际地质情况分析的异常速度变化等.当前的地震资料处理系统中,速度分析通常采用交互速度分析的方法,通过实时、人机交互的方式进行速度分析,大大提高了速度分析的效率.为了到准确的速度分析结果,必须针对实际资料情况,对速度分析的影响因素进行认真分析和总结,并选用合适的控制方法进行处理仍然是实际资料处理中交互速度分析的重点和难点.这里基于GeoEast软件系统的交互速度分析模块,通过对实际资料的处理,对交互速度分析的影响因素进行分析总结,提出一些实用的控制方法,取得了较好的处理效果,对实际生产中进行交互速度分析提供了一定的借鉴.