利用DE算法反演地壳速度模型和地震定位

利用差异演化（Differential Evolution）非线性全局优化算法,设计了一种反演地壳速度模型和进行地震定位的方法,并给出了反演结果的具体分析.利用有限差分算法计算速度模型的走时场,可以节省大量的计算量,加快计算过程.反演得到的地壳速度模型和地震的震源参数可以直接用于地震层析成像研究,还可以利用地震层析成像得到的三维速度结构对地震重新定位,从而得到较为精确的震源参数.地壳速度模型的反演方法也可以用于三维速度结构的反演.     

求解二次方程的二维VTI介质qSV波和qSH波走时快速扫描算法

地震波走时计算在观测系统设计、偏移成像、速度模型走时反演和地震定位等方面起到重要作用.各向异性广泛存在于地球介质中,影响地震波传播的振幅和走时,忽略各向异性的影响将对成像、反演以及地震定位等造成一定的误差.因此对于高分辨率成像和反演,走时计算中考虑各向异性十分重要.快速扫描法不需要存储和追踪波前面信息,在各向异性初至波...     

无需测速的微震源反演数学模型研究

微震源反演数学模型、反演算法等对象是微震源定位误差的重要来源。针对P波速度易衰减、首波到时数据拾取误差较大的情况,基于到时差模型(ATD)和P波到时方程组,建立到时差比值法反演数学模型(ATDRM),从目标函数中消除了P波速度和发震时刻等参数;同时,引入范数概念,得到改进的L1、L2、L3、L4范数模型,设计一系列反演模型对比实验和反演算法对比实验综合分析研究这些模型的优越性。工程数据显示：ATDRM模型的定位效果整体比经典ATD模型更好,ATDRM-L1模型震源误差可减少13.437 0 m;反演模型的定位误差受反演算法影响较大,单形替换法相比遗传算法(GA)、非线性最小二乘法(NLSM)、模拟退火算法(SA)等方法定位精度更高,稳定性更好;在应用单形替换法求解模型时,反演误差会随着范数参数N的增加(L1→L4)呈现先下降再上升的现象;ATDRM模型及其范式形式对提高微震源定位精度有一定价值。     

水力压裂对速度场及微地震定位的影响

水力压裂是页岩气开发过程中的核心增产技术,微地震则广泛用于压裂分析、水驱前缘监测和储层描述.微地震反演过程中,用于反演的速度模型往往基于测井、地震或标定炮资料构建,忽略了压裂过程中裂缝及孔隙流体压力变化对地层速度的影响.本文首先基于物质守恒、渗流理论和断裂力学模拟三维水力压裂过程,得到地下裂缝发育特征和孔隙压力分布.继而根据Coates-Schoenberg方法和裂缝柔量参数计算裂缝和孔隙压力对速度场的影响,得到压裂过程中的实时速度模型.最后利用三维射线追踪方法正演微地震走时和方位信息,并采用常规微地震定位方法反演震源位置及进行误差分析.数值模拟结果表明,检波器空间分布影响定位精度,常规方法的定位误差随射线路径在压裂带中传播距离增加而变大,且不同压裂阶段的多点反演法与单点极化法精度相当.     

川西龙门山及邻区地壳上地幔各向异性地震P波走时层析成像研究

经典的地震层析成像假定介质为各向同性,通过走时反演确定地球介质的非均匀结构,得到的仅是近似地球模型。如果各向异性较强时,应用基于各向同性假设的层析成像算法,可能导致错误的结果。非均匀与各向异性效应是耦合的,如果仅考虑非均匀效应则各向异性结构可能映射到非均匀结构中造成非均匀速度结构的误差,反之亦然。因此,高分辨率的走时层析成像必须同时考虑非均匀和各向异性两种效应。同时反演非均匀和各向异性结构(即各向异性层析成像),不仅可以获得可靠的各向同性速度结构,同时可以确定各向异性结构。相对于S波偏振分析,体波走时方法基于不同的数据集,能提供独立的地震各向异性观测证据。利用地震走时层析成像方法同时研究介质的非均匀性和各向异性,对于认识地球的结构及动力学过程都具有非常重要的意义。     

微地震监测定位精度分析

随着非常规致密砂岩气、页岩气藏的开采开发,压裂技术在储层改造中起着举足轻重的作用,而微地震监测技术是评价压裂施工效果的关键且即时的技术之一.根据微地震监测处理高精度地反演微震位置,从而预测压裂裂缝的发展趋势及区域,对压裂施工效果进行跟踪及评判,同时也为后期油气藏的开采和开发提供技术指导.定位精度直接影响地下裂缝的分布特征,错误或精度不高的定位结果,必将导致对裂缝趋势的误判.文章结合理论和数值模拟方法,对初至拾取精度的影响因素进行了分析,讨论初至误差对定位精度的影响.同时结合地层岩石物理特性、射孔资料对速度模型的校正、速度各向异性、地层倾角、多段压裂等因素,分析了这些因素对精细速度模型及定位精度的影响.最后结合定位方法本身所存在的局限,探讨反演方法及方位角对定位精度的影响.通过理论及数值模拟分析表明,初至误差、速度模型精度及定位方法对定位精度有着紧密关系,并将其归类为可控误差及系统误差,通过区别对待可控误差和系统误差,可最终为高精度微地震监测定位技术的研究及应用提供指导.     

各向异性TI介质qP反射波走时层析成像

地震走时层析成像是反演地层各向异性参数分布的有效方法,但是关于地震各向异性介质走时层析成像的研究并不多,其技术远远没有达到成熟的阶段.在野外数据采集时,地表反射波观测方式相对井间和垂直地震剖面观测方式的成本更低,利用qP反射波走时反演各向异性参数具有更加广泛的实用价值.本文实现的TI介质地震走时层析成像方法结合了TI介质反射波射线追踪算法、走时扰动方程和非线性共轭梯度算法,它可以对任意强度的TI介质模型进行反演,文中尝试利用qP反射波走时重建TI介质模型的参数图像.利用qP反射波对层状介质模型和块状异常体模型进行走时反演,由于qP波相速度对弹性模量参数和Thomsen参数的偏微分不同,所以可以分别反演弹性模量参数和Thomsen参数.数值模拟结果表明:利用qP反射波可以反演出TI介质模型的弹性模量参数与Thomsen参数,不同模型的走时迭代反演达到了较好的收敛效果,与各向同性介质走时反演结果相比较,各向异性介质走时反演结果具有较好的识别能力.     

干涉走时微地震震源定位方法

本文基于地震波场干涉原理,建立了干涉走时微地震震源定位方法.该方法将两个接收点相对于一个微地震事件的走时差(称为干涉走时)的扰动作为残差函数,通过迭代求解最小残差函数,最终获得震源的空间位置.干涉走时震源定位方法利用两个接收点的到时差消除发震时刻未知和速度模型误差的影响,简化了震源定位算法.数值计算表明,本文提出的干涉走时定位方法在速度模型有误差的情况下仍然可以获得准确的微地震震源定位.     

VTI介质SH-SH波地震反演方法研究

近年来,随着横波可控震源技术的发展,国内外已经实现了纯横波地震勘探.相较于地震纵波,地震横波对横波阻抗、横波速度尤其是各向异性参数变化更为敏感,因此地震横波能够用来更好地估算上述地层参数.VTI(具有垂直对称轴的横向各向同性)是地层介质中广泛存在的一种各向异性形式,对振幅随偏移距变化(AVO)影响显著.本文提出了一种改进的VTI介质SH-SH波反射系数近似公式,新公式具有较高的精度且仅包含两项待求参数：横波阻抗和水平横波(SH波)速度.基于新方程建立了VTI介质SH-SH波反演方法,该方法相比VTI介质的PP波反演不确定性明显下降,同时降低了常规PP波各向异性反演对大角度数据的要求.为了获得独立的横波各向异性参数,进一步地提出了一种基于岩石物理关系的横波各向异性参数估算方法.合成地震数据测试和柴达木盆地九分量地震勘探实际地震数据应用结果表明,新方法能够准确地预测地层的横波阻抗、水平横波(SH波)速度、各向异性参数,为各向异性地层的岩性解释和油气储层预测提供了可靠的解决方案,从而深化了横波地震勘探的应用潜力.     

球坐标系下多震相走时三参数同时反演成像

球坐标系下多震相走时三参数(速度、震源位置和反射界面)同时反演需要解决两个关键问题:(1)球坐标系下3D速度模型中多次透射、反射(折射)及转换波精确、快速的射线追踪;(2)同时反演时三种不同参数间的强耦合问题.为此,我们将直角坐标系下分区多步不规则最短路径算法推广至球坐标系中,进行区域或者全球尺度的多震相射线追踪.然后将其与适合多参数同时反演的子空间算法相结合,形成一种球坐标系下联合多震相走时三参数同时反演的方法技术.与双参数(速度和反射界面或速度和震源位置)同时反演的数值模拟对比分析显示:三参数与双参数的同时反演结果大体接近,并且它们对到时数据中可容许的随机噪声不太敏感.结果说明本文中的同时反演成像为一种提高成像分辨率,同时反演速度、震源位置和反射界面的有效方法.     

一种改进的基于网格搜索的微地震震源定位方法

震源定位是微地震监测技术要解决的主要问题.目前,井下微地震监测多采用走时拟合法计算震源位置.常规方法受到环境噪声、初至拾取误差、速度模型误差等因素的影响,定位结果存在一定误差.为了提高定位精度,本文提出了一种改进的基于网格搜索的微地震震源定位方法.本文方法根据P波的偏振特征参数计算概率密度函数求取震源方位角,并采用改进的目标函数和搜索算法计算震源的径向距离和深度.模型数据和实际资料的处理结果表明,本文方法具有较强的抗噪性,计算得到的震源方位角更加接近真实值;与常规目标函数相比,本文方法采用的目标函数具有更好的收敛性,其定位结果受初至拾取误差和速度模型误差的影响更小;本文提出的搜索算法能够消除由于错误拾取造成的观测到时中的异常值对定位结果的影响.     

三维地震与地面微地震联合校正方法

由于地面微地震监测台站布设在地表,会受到地表起伏、低降速带厚度和速度变化的影响,降低了微地震事件的识别准确度和定位精度,限制了地面微地震监测技术在复杂地表地区的应用.因此,将三维地震勘探技术的思路引入到地面微地震监测中,提出了三维地震与地面微地震联合校正方法,将油气勘探和开发技术更加紧密地结合在一起.根据三维地震数据和低降速带测量数据,通过约束层析反演方法建立精确的近地表速度模型,将地面微地震台站从起伏地表校正到高速层中的平滑基准面上,有效消除复杂近地表的影响.其次,根据射孔数据和声波测井速度信息,通过非线性反演方法建立最优速度模型,由于已经消除复杂近地表的影响,在进行速度模型优化时不需要考虑近地表的影响,因而建立的速度模型更加准确.最后,在精确速度模型的基础上,通过互相关方法求取剩余静校正量,进一步消除了复杂近地表和速度模型近似误差的影响.三维地震与地面微地震联合校正方法采用逐步校正的思路,能够有效消除复杂近地表的影响,提高微地震数据的品质和速度模型的精确度,保证了微地震事件的定位精度,具有良好的应用前景.     

基于时频稀疏性分析法的低信噪比微震事件识别与恢复

微震监测是直观评价压裂过程和压裂效果的有效手段.微震事件识别是微震监测的首要步骤.然而对于低信噪比微震监测数据,常规识别方法很难取得满意效果.基于微震事件在时频域中的稀疏性,本文提出利用Renyi熵值表示微震监测数据的时频稀疏程度,并以时频距离为约束条件,建立以低熵值的道数为判别阈值的目标函数.本文方法能在识别出微震事件的同时,恢复出较为清晰的微震事件.通过数值计算和对实际监测数据的测试,表明该方法对低信噪比的微震监测数据有较好的处理效果.     

Locating microseismic events using borehole data

Constraining microseismic hypocentres in and around hydrocarbon reservoirs and their overburdens is essential for the monitoring of deformation related to hydraulic fracturing, production and injection and the assessment of reservoir security for CO₂ and wastewater storage. Microseismic monitoring in hydrocarbon reservoirs can be achieved via a variety of surface and subsurface acquisition geometries. In this study we use data from a single, subsurface, vertical array of sensors. We test an existing technique that uses a 1D velocity model to constrain locations by minimizing differential S‐to‐P arrival times for individual sensors. We show that small errors in either arrival time picks or the velocity model can lead to large errors in depth, especially near velocity model discontinuities where events tend to cluster. To address this issue we develop two methods that use all available arrival times simultaneously in the inversion, thus maximizing the number of potential constraints from to N, where N is the number of phase picks. The first approach minimizes all available arrival time pairs whilst the second approach, the equal distance time (EDT) method defines the hypocentre as the point where the maximum number of arrival time surfaces intersect. We test and compare the new location procedures with locations using differential S‐to‐P times at each individual sensor on a microseismic data set recorded by a vertical array of sensors at the Ekofisk reservoir in the North Sea. Specifically, we test each procedure's sensitivity to perturbations in measured arrival times and the velocity model using Monte Carlo analysis. In general, location uncertainties increase with increasing raypath length. We show that errors in velocity model estimates are the most significant source of uncertainty in source location with these experiments. Our tests show that hypocentres determined by the new procedures are less sensitive to erroneous measurements and velocity model uncertainties thus reducing the potential for misinterpretation of the results.     

Cross double‐difference inversion for simultaneous velocity model update and microseismic event location

Microseismic monitoring is an approach for mapping hydraulic fracturing. Detecting the accurate locations of microseismic events relies on an accurate velocity model. The one‐dimensional layered velocity model is generally obtained by model calibration from inverting perforation data. However, perforation shots may only illuminate the layers between the perforation shots and the recording receivers with limited raypath coverage in a downhole monitoring problem. Some of the microseismic events may occur outside of the depth range of these layers. To derive an accurate velocity model covering all of the microseismic events and locating events at the same time, we apply the cross double‐difference method for the simultaneous inversion of a velocity model and event locations using both perforation shots and microseismic data. The cross double‐difference method could provide accurate locations in both the relative and absolute sense, utilizing cross traveltime differences between P and S phases over different events. At the downhole monitoring scale, the number of cross traveltime differences is sufficiently large to constrain events locations and velocity model as well. In this study, we assume that the layer thickness is known, and velocities of P‐ and S‐wave are inverted. Different simultaneous inversion methods based on the Geiger's, double‐difference, and cross double‐difference algorithms have been compared with the same input data. Synthetic and field data experiments suggest that combining both perforation shots and microseismic data for the simultaneous cross double‐difference inversion of the velocity model and event locations is available for overcoming the trade‐offs in solutions and producing reliable results.     

卷积神经网络在地面微地震多道P波极性分类中的应用

微地震监测技术是监测水力压裂过程、评价压裂效果的重要手段。对于地面监测,P波极性能够直接、快速地反演震源机制,同时极性校正能够提高绕射叠加定位方法的成像精度。因此,准确而迅速地确定P波极性对地面微地震实时监测具有重要意义。卷积神经网络是一种深度学习算法,具有强大的特征学习与分类能力,可用来确定微地震事件的P波极性。地面监测多采用星型、网格型等规则观测系统,本文使用目标道及其相邻检波器记录作为输入样本,构建基于卷积神经网络的多道P波极性分类网络模型。实际数据应用结果表明,相比于单道记录的网络模型,多道的网络模型能够将目标道与相邻道相结合来预测目标道的极性,提高规则观测系统下地面微地震P波极性分类的准确率。     

Automatic event detection in low SNR microseismic signals based on multi-scale permutation entropy and a support vector machine

Microseismic monitoring is an effective means for providing early warning of rock or coal dynamical disasters, and its first step is microseismic event detection, although low SNR microseismic signals often cannot effectively be detected by routine methods. To solve this problem, this paper presents permutation entropy and a support vector machine to detect low SNR microseismic events. First, an extraction method of signal features based on multi-scale permutation entropy is proposed by studying the influence of the scale factor on the signal permutation entropy. Second, the detection model of low SNR microseismic events based on the least squares support vector machine is built by performing a multi-scale permutation entropy calculation for the collected vibration signals, constructing a feature vector set of signals. Finally, a comparative analysis of the microseismic events and noise signals in the experiment proves that the different characteristics of the two can be fully expressed by using multi-scale permutation entropy. The detection model of microseismic events combined with the support vector machine, which has the features of high classification accuracy and fast real-time algorithms, can meet the requirements of online, real-time extractions of microseismic events.     

Effective anisotropic velocity model from surface monitoring of microseismic events

We develop a methodology to obtain a consistent velocity model from calibration shots or microseismicity observed on a buried array. Using a layered 1D isotropic model derived from checkshots as an initial velocity model, we invert P‐wave arrival times to obtain effective anisotropic parameters with a vertical axis of symmetry (VTI). The nonlinear inversion uses iteration between linearized inversion for anisotropic parameters and origin times or depths, which is specific to microseismic monitoring. We apply this technique to multiple microseismic events from several treatments within a buried array. The joint inversion of selected events shows a largely reduced RMS error indicating that we can obtain robust estimates of anisotropic parameters, however we do not show improved source locations. For joint inversion of multiple microseismic events we obtained Thomsen anisotropic parameters ε of 0.15 and δ of 0.05, which are consistent with values observed in active seismic surveys. These values allow us to locate microseismic events from multiple hydraulic fracture treatments separated across thousands of metres with a single velocity model. As a result, we invert the effective anisotropy for the buried array region and are able to provide a more consistent microseismicity mapping for past and future hydraulic fracture stimulations.     

The structure of the Lomonosov volcanic pipe in the Arkhangel’sk diamond province from anomalies of the microseismic field

This paper presents results from a study of the Lomonosov volcanic pipe as derived from anomalies of the microseismic field. Microseismic sounding revealed that this volcanic pipe is a cone-shaped body with a small gradient of microseismic intensity motion (2 to 5 dB). Discontinuities generally show greater contrasts compared with the variations of microseismic motion in the pipe body. Comparison of the results of this microseismic sounding with other geological and geophysical data showed that the intensities of the microseismic field along lines that traversed the pipe reflect realistic structures of a kimberlite pipe and the host rocks. The method of microseismic sounding was used to reconstruct the deeper structure of the volcanic pipe and the host rocks down to depths greater than 2 km. We estimated the velocity contrast and the errors involved in the identification of vertical boundaries of the pipe. The volcanic pipe has a shape that is consistent with a nearly vertical source situated at a depth of a few hundred meters. This is hypothesized to be a typical occurrence for other diamond-bearing pipes as well.     

邻近算法在微地震震源位置和一维速度模型同时反演中的应用

微地震事件的空间分布可以用来监测水力压裂过程中裂缝的发育情况。因此,震源定位是微震监测中重要的环节。震源定位依赖准确的速度模型,而震源位置和速度模型的耦合易导致线性迭代的同时反演方法陷入局部极小值。邻近算法作为一种非线性全局优化算法,能够最大程度地避免陷入局部最优解。本文将邻近算法应用于单井监测的微震定位和一维速度模型同时反演,首先利用邻近算法搜索一维速度模型,再使用网格搜索方法进行震源定位,并根据定位的走时残差产生新的速度模型,最后通过若干次迭代使其收敛到最优解。理论和实际数据结果均表明该方法能够避免局部最优解,得到较为可靠的震源位置和一维速度模型。