Using multi-wave and multi-component seismic data for reservoir prediction, fracture detection and fluid identification has unique advantages. However, before the interpretation of joint seismic data of horizontal and horizontal waves, it is necessary to first solve the matching problem of horizontal and horizontal waves. This paper introduces a high precision multi-wave matching method based on singular value decomposition. By singular value decomposition (SVD), the method constructs the similarity function between longitudinal wave (PP) and converted wave (PS) maximization and imaging profile as the matching objective function to compensate the difference between reflection coefficients of longitudinal wave and converted wave, and matches through global optimization. This method overcomes the disadvantages caused by amplitude, phase, waveform, velocity and other big differences between longitudinal wave and shear wave when PP wave and PS wave are matched in time domain. An example test shows that the matching accuracy of this method is greatly improved, and it can provide high quality seismic data for joint inversion of vertical and horizontal waves and extraction of joint attributes of multiple waves, and good results are obtained.

页岩总有机碳(TOC)含量是反映页岩生烃潜力及页岩气富集程度的关键参数之一.四川盆地渝西地区Z井区的页岩气勘探,存在钻探程度低、地质资料少和岩心样品实验分析数据不全等不利因素,难以利用测井资料得到精确的总有机碳含量曲线.而通过地震正演、地震多属性反演和叠前反演等方法预测的总有机碳含量又存在精度较低的问题.为了实现总有机碳含量精细预测,提出了一种基于粒子群(PSO)优化支持向量机(SVM)算法的页岩气总有机碳含量计算方法.首先,根据总有机碳含量与测井资料的交会关系,确定自然伽马、密度和纵横波速度比等与计算总有机碳含量相关的敏感测井参数,利用支持向量机和粒子群优化算法的方法原理,建立适用于研究区与计算总有机碳含量相应的粒子群优化支持向量机算法;其次,采用该算法计算总有机碳含量测井曲线并与岩心总有机碳含量数据进行对比以修正算法的预测精度;最后,在常规地震反演数据体基础上,利用粒子群优化支持向量机算法计算出储层总有机碳含量数据体,进而开展页岩总有机碳含量有利勘探区的预测与页岩气储层的评价.研究结果表明,粒子群优化支持向量机算法预测总有机碳含量曲线与岩心实测总有机碳含量较为吻合,误差较小,同时,通过地震资料预测总有机碳含量的结果与测井解释的总有机碳含量结果对应较好.表明在非均质性较强的页岩气储层中,利用粒子群优化支持向量机算法进行总有机碳含量预测,可以有效提高页岩气储层总有机碳含量的预测精度,对四川盆地渝西地区页岩气勘探开发具有一定的指导意义.

An approach to pseudo-acoustic log curve construction based on probabilistic neural networks(PNN) is presented in the paper.Firstly,the basic mathematical model of PNN is discussed.Then,a multi-input and single-output PNN network topology which is fit multi-source logging information fusion is designed on the basis of the model.After that,the output of the new model with the minimum fit error criterion is derived using PNN interpolation function.Finally,the actual logging data is processed by the model,and a fast pseudo-acoustic curve construction is adaptively obtained.The processing results show the rationality and effectiveness of the method.

The conventional non-linear seismic inversion methods are low in convergence and sometimes will result in the problem of local extremum.To solve these problems,we developed a non-linear seismic inversion of hybrid intelligent optimization with the particle warm optimization algorithm and the Guo's algorithm integrated.The particle warm algorithm is characterized by higher objective in solution upgrading and rapid convergence,while the Guo's algorithm constructs a multi-parent combination crossover and adopts a colony mountain climbing search strategy,thus is high in accuracy of solution.The hybrid intelligent algorithm uses the particle warm optimal algorithm as the framework and takes advantage of the optimization mechanism of the Guo's algorithm.We performed function optimization test,trial calculation with the theoretical model and real data inversion processing.The results show that this method has the advantages of high efficiency and strong capacity of global optimization,thus is suitable for complex seismic inversion.

In order to get accurate calculation result of seismic interval velocity by use of velocity spectrum,this paper,taking the GeoMountain Seismic Interpreter System as a platform,puts forward a new calculation method of interval velocity including general DIX interval velocity calculation method restricted by regional empirical value,backstepping calculation method through the known interval velocity spectrum based on general DIX formula,horizon-based calculation method of interval velocity and azimuth smoothening etc.Examined by the actual structural map of Mopan-Laowan working area in East Sichuan basin,the interval velocity calculated by this method showed a better rule in lateral variation and coincided better with the actual geological conditions.

At present,there are some limitations on mountain seismic data interpretation by use of commercial interpretation softwares at home and abroad.Although Sichuan Geophysical Prospecting Company has already accumulated lots of producing techniques and scientific research achievements in the way of mountain seismic interpretation for many years,it was inconvenient for integrated application of certain techniques especially some key techniques.As a result,it is an important project to integrate mountain seismic interpretation platform into one unit so as to make it tangible.This paper,through a thorough analysis on basic platforms of current main commercial software and in combination with the development mode of Sichuan and Chongqing mountain geophysical prospecting,probes out a set of software architecture design with basic platform as well as function plug-in and forms software system for the GeoMountain Interpreter.This interpretation platform solves the problems in the development and integration of this software in a better way and with wonderful extensibility.Based on this interpretation platform,many function plug-ins are developed such as well analysis,structure interpretation,prediction on reservoir attributes and multiwave etc.,and this system has already achieved better application effect on seismic interpretation for over 10 projects.

It was important of time-frequency analytical technique in predicting reservoir,and in expressing the seismic information in time domain and frequency domain at the same time.The seismic information was expressed in time-frequency domain,and was not expressed in time domain.High-accuracy time-frequency analysis method S-transform was selected because traditional time-frequency theory could not overcome the difficult and develop time resolution and frequency resolution difficulty.The flow applying S-transform time-frequency analysis method is discussed as it is used for predicting organic reservoirs,and the result is in accordance with actual drilling.

Multi-wave interpretation is hard to be done smoothly for lack of relatively perfect multi-wave interpretation software.Therefore,to develop multi-wave interpretation software with independent intellectual property right is of great importance in providing a practical tool for three component seismic data analysis as well as a research platform for multi-wave technique and in filling gaps of domestic multi-wave software.Based on the reference of the introduced commercial softwares and our own accumulated techniques on multi-wave interpretation,this paper not only carries out research into such key techniques as multi-wave synthetic seismograph,horizon calibration,horizon joint correlation as well as matching and AVO linear joint inversion based on approximate formula of PP wave and PS wave's reflection coefficient but also gets an interactive method meeting the requirement for the interpretation of reverse fault in mountain areas.On this basis,a set of 2D three component interpretation software was developed which can finish 2D three component seismic data interpretation as well as multi-wave joint inversion.As a result,the 2D three component seismic data in Guang'an region of Sichuan basin has been interpreted,multi-wave joint inversion of the target gas-bearing layer has been done and a gas-bearing range has neen interpreted by use of this software.

随着地震勘探技术的进步,多分量地震勘探技术越来越受到人们的关注,逐渐成为当前地震勘探的热点,但由于转换波的下行波是纵波,上行波是横波,横波的剪切波动力学特征与纵波不相同、在同一地层的纵横波速度的差异表现在运动学特征上与常规纵波也不一样、此外纵横波在相同地层的耗散也不相同,因此,转换波剖面与常规纵波剖面有较大差别。正确识别转换波剖面的地质层位是多分量解释的首要任务,也是当前多分量地震勘探需要突破的一个技术难点。为此,以川中地区GA构造2D3C为例,在前人经验的基础上,综合运用了多种转换波层位标定对比技术,实践证明对该地区的转换波层位标定正确可靠,收到了良好的效果。

Independent component analysis(ICA)is a recently devel- oped method based on higher order statistical analysis.ICA can separate signals that are statistically independent but linearly mixed.Seismic signals and random noises are generally non- gaussain and are statistically independent.Based on an analysis of the characteristics of seismic signals and random noises,the author adopted fast ICA that are based on minimum mutual in- formation to eliminate random noises from seismic data.The feasibility of the method is verified with model and real data.

The K-L transformation uses the coherence of adjacent seismic traces to remove the random noise. But the de-noise effect is not good for sloping and bending event reflection. Although the advanced time-variation dip sweep stack K-L transformation can remove random noises, the characteristics of effective signals and random noises in frequency domain is not taken into consideration, making the high-frequency effective signals lost. Because the wavelet transformation has a good ability in time-frequency analysis, the K-L transformation in wavelet domain can remove noises in time and frequency domain separately. The principles of suppressing random noises with K-L transformation in wavelet conversion domain are that 1) wavelet decomposition is carried out on seismic signals to form wavelet packet sections in time sharing and frequency division, 2) K-L transformation is utilized to remove noises on sections, and 3) the de-noise wavelet packet sections are reconstituted into seismic sections to remove random noises. The theoretical model computation and actual data processing show that the K-L transformation in wavelet conversion domain can remove random noises effectively and preserve the effective high-frequency signals simultaneously.

In interpretation of conventional seismic data, p-wave is used to detect lithology, gas and oil. The results are not one and only. Using multi -components seismic data which have much seismic information can reduces possible mutli-result. In this paper , we use p -wave and ps -wave velocity of multi -components seismic data and their velocity ratio, Poisson ratio, quadrature trace and impedance of p -wave and ps -wave to predict gas and oil in reservoir. The predicted results are the same as that of drilling. This study shows that using multi -components seismic data can enhance the precision and reliability of prediction of reservoir.

PreviousNext No AccessSEG Technical Program Expanded Abstracts 20062D three components seismic exploration case for clastic rock reservoir in Guangan structure, Sichuan basinAuthors: Li ZhongXie FangLi YalinWang HongyanHuang DongshanWang YuhuaLi ZhongSichuan Geophysical CompanySearch for more papers by this author, Xie FangSichuan Geophysical CompanySearch for more papers by this author, Li YalinSichuan Geophysical CompanySearch for more papers by this author, Wang HongyanSichuan Geophysical CompanySearch for more papers by this author, Huang DongshanSichuan Geophysical CompanySearch for more papers by this author, and Wang YuhuaSichuan Geophysical CompanySearch for more papers by this authorhttps://doi.org/10.1190/1.2369743 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract The paper presents multicomponent seismic acquisition test and the preliminary results for the clastic reservoir in Guangan structure of Sihcuan Basin. In 2005, our company acquired 2D three component data with high quality with the digital geophone, and applied micro‐VSP method to investigate shear wave near‐surface velocity structure. X component and Y component seismic section obtained by the multicomponent data processing technique plausibly reflected the formation anisotropy, and the lithology and fluid detection study can be completed by the joint interpretation of the PP‐wave and PS‐wave reflection sections. P‐wave and S‐wave acoustic impedance inversion results reflected the reservoir properties accurately, and the inversion results are consistent with the drilling results. The present study results indicate that the multicomponent seismic will become a practical and effective method for lithology and fluid detection.Permalink: https://doi.org/10.1190/1.2369743FiguresReferencesRelatedDetails SEG Technical Program Expanded Abstracts 2006ISSN (print):1052-3812 ISSN (online):1949-4645Copyright: 2006 Pages: 3541 publication data© 2006 Copyright © 2006 Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished: 06 Oct 2006 CITATION INFORMATION Li Zhong, Xie Fang, Li Yalin, Wang Hongyan, Huang Dongshan, and Wang Yuhua, (2006), "2D three components seismic exploration case for clastic rock reservoir in Guangan structure, Sichuan basin," SEG Technical Program Expanded Abstracts : 1233-1237. https://doi.org/10.1190/1.2369743 Plain-Language Summary PDF DownloadLoading ...

The genetic algorithm is a stochastic search method of global optimization, but also it has the disadvantages of low local search ability and precision. In order to solving the disadvantages this paper introduces pattern search, using the strong local search ability and high precision of pattern search to offset it. First of all, using generitc algorithm to compute a number of generations, and take all searched points as the first points of pattern search, then quicken convergent velocity. The analysis of theorized model and example computing validate the method of mixed optimum algorithm.

The most common multiwave exploration at present uses P-wave source shooting technique and three-component geophones, which receive not only P-wave signals but also converted shear wave signals. Mutiwave multicomponent seismic exploration is to comprehensively utilize the P-wave and shear wave signals. In comparison with the conventional P-wave exploration, multiwave seismic exploration can obtain more subsurface information, and the combination of P-wave and shear wave helps to more accurately determine the properties of reservoir and fluids and reduce ambiguity of interpretation. This paper introduces the preliminary application of the mutiwave multicomponent seismic technology in Guang'an structure in the Sichuan Basin. Based on the results of multiwave multicomponent seismic acquisition and processing in this block, horizon correlation of P-wave and converted wave, i.e. P-SV wave, and horizon calibration of converted wave are carried out and compressed section is generated. Attribute parameters, such as compressional to shear velocity ratio, λ_ρ and μ_ρ are extracted through comparative analysis of P-wave converted section and combined inversion of P-wave and converted wave, i.e. P-SV wave. The reservoirs in the 6th member of Xujiahe Fm are predicted and preliminary results have been obtained.

This paper introduces the application of multi-component technology in the exploration of Guangan structure. On the basis of quality data from proper data acquisition and processing, we performed horizon matching between P- and converted-waves, horizon calibration for converted-waves, and construction of compressed sections. Attributes such as velocity ratio of P- and S-wave, λρ and μρ were extracted by comparison between P-wave and converted-wave sections and joint inversion of P-wave and converted-waves. The method has been applied in the prediction for reservoirs of the sixth segment of the Xu Formation.