河流相砂泥岩薄互层地震反射特征研究

A sedimentary geological model is established in order to study the seismic reflection characteristics of channel sand bodies. Synthetic seismic shot gathers are simulated using the acoustic wave equation and then are prestack time migrated. On the imaged data, the reflection characteristics and instantaneous attributes are analyzed and log-constrained impedance inversion is tested. Because of wave field interference, the experimental results show that seismic events do not definitely correspond to the channel sand bodies and that seismic modes of occurrence do not represent the actual ones. The seismic events formed by wave interference may lead to errors and pitfalls in sand body interpretation. The corresponding relations between instantaneous seismic attributes and sedimentary sands are not well established. Log-constrained impedance inversion improves the resolution of channel sands. However, if the inverted resolution is forced to be too high, artifacts related to the initial model may occur.     

Active Source Seismic Identification and Automatic Picking of the P-wave First Arrival Using a Convolutional Neural Network

In seismic data processing, picking of the P-wave first arrivals takes up plenty of time and labor, and its accuracy plays a key role in imaging seismic structures. Based on the convolution neural network (CNN), we propose a new method to pick up the P-wave first arrivals automatically. Emitted from MINI28 vibroseis in the Jingdezhen seismic experiment, the vertical component of seismic waveforms recorded by EPS 32-bit portable seismometers are used for manually picking up the first arrivals (a total of 7242). Based on these arrivals, we establish the training and testing sets, including 25,290 event samples and 710,616 noise samples (length of each sample:2s). After 3,000 steps of training, we obtain a convergent CNN model, which can automatically classify seismic events and noise samples with high accuracy (> 99%). With the trained CNN model, we scan continuous seismic records and take the maximum output (probability of a seismic event) as the P-wave first arrival time. Compared with STA/LTA (short time average/long time average), our method shows higher precision and stronger anti-noise ability, especially with the low SNR seismic data. This CNN method is of great significance for promoting the intellectualization of seismic data processing, improving the resolution of seismic imaging, and promoting the joint inversion of active and passive sources.     

Seismic identification of channel sandbodies in the Fuyang oil layer in North Songliao Basin, China

The Fuyang oil-layer in North Songliao Basin is characterized by thin interbedded sands and shales, strong lateral variation, strong reservoir heterogeniety, and so on. The thickness of individual sand layers is generally 3 - 5 m. Identifying the channel sand-bodies of the Fuyang oil layer using seismic techniques is very difficult due to the low seismic resolution. Taking the GTZ area as an example, we discuss the genetic characteristics of the channel sand-bodies and point out the real difficulty in using seismic techniques to predict the channel sand-bodies. Two methods for the identification of channels are presented： frequency spectrum imaging and pre-stack azimuthal anisotropy. Identifying the channel sand-bodies in Fuyu oil-layer using the two seismic methods results in a success rate up to 80% compared with well data.     

Simultaneous Denoising and Interpolation of Seismic Data via the Deep Learning Method

Utilizing data from controlled seismic sources to image the subsurface structures and invert the physical properties of the subsurface media is a major effort in exploration geophysics. Dense seismic records with high signal-to-noise ratio (SNR) and high fidelity helps in producing high quality imaging results. Therefore, seismic data denoising and missing traces reconstruction are significant for seismic data processing. Traditional denoising and interpolation methods rarely occasioned rely on noise level estimations, thus requiring heavy manual work to deal with records and the selection of optimal parameters. We propose a simultaneous denoising and interpolation method based on deep learning. For noisy records with missing traces, we adopt an iterative alternating optimization strategy and separate the objective function of the data restoring problem into two sub-problems. The seismic records can be reconstructed by solving a least-square problem and applying a set of pre-trained denoising models alternatively and iteratively.We demonstrate this method with synthetic and field data.     

Characteristics analysis on high density spatial sampling seismic data

China＇s continental deposition basins are characterized by complex geological structures and various reservoir lithologies. Therefore, high precision exploration methods are needed. High density spatial sampling is a new technology to increase the accuracy of seismic exploration. We briefly discuss point source and receiver technology, analyze the high density spatial sampling in situ method, introduce the symmetric sampling principles presented by Gijs J. O. Vermeer, and discuss high density spatial sampling technology from the point of view of wave field continuity. We emphasize the analysis of the high density spatial sampling characteristics, including the high density first break advantages for investigation of near surface structure, improving static correction precision, the use of dense receiver spacing at short offsets to increase the effective coverage at shallow depth, and the accuracy of reflection imaging. Coherent noise is not aliased and the noise analysis precision and suppression increases as a result. High density spatial sampling enhances wave field continuity and the accuracy of various mathematical transforms, which benefits wave field separation. Finally, we point out that the difficult part of high density spatial sampling technology is the data processing. More research needs to be done on the methods of analyzing and processing huge amounts of seismic data.     

Automatic onset phase picking for portable seismic array observation

Automatic phase picking is a critical procedure for seismic data processing, especially for a huge amount of seismic data recorded by a large-scale portable seismic array. In this study is presented a new method used for automatic accurate onset phase picking based on the proporty of dense seismic array observations. In our method, the Akaike＇s information criterion （AIC） for the single channel observation and the least-squares cross-correlation for the multi-channel observation are combined together. The tests by the seismic array observation data after triggering with the short-term average/long-term average （STA/LTA） technique show that the phase picking error is less than 0.3 s for local events by using the single channel AIC algorithm. In terms of multi-channel least-squares cross-correlation technique, the clear teleseismic P onset can be detected reliably. Even for the teleseismic records with high noise level, our algorithm is also able to effectually avoid manual misdetections.     

Wavefield continuation datuming using a near surface model

When topography and low velocity zone differences vary greatly, conventional vertical static time shifts will cause wavefield distortion and influence wave equation seismic imaging for seismic data acquired on a complex near surface. In this paper, we propose an approach to datum correction that combines a joint tomography inversion with wavefield continuation to solve the static problem for seismic data on rugged acquisition topography. First, the near surface model is obtained by refracted wave tomography inversion. Second, the wavefield of sources and receivers are continued downward and upward to accomplish datum correction starting from a flat surface and locating the datum above topography. Based on the reciprocal theorem, Huygens＇ and Fresnel principles, the location of sources and receivers, and regarding the recorded data on the surface as a secondary emission, the sources and receivers are upward-continued to the datum above topography respectively. Thus, the datum correction using joint tomography inversion and wavefield continuation with the condition of a complex near surface is accomplished.     

3-D physical model in strong ground motion numerical simulation： A case study of Kunming basin

Seismic hazard assessment based on urban active faults can provide scientific bases for city planning and projectconstruction,while numerical simulation of strong ground motion is an important method for seismic hazard pre-diction and assessment.A 3-D physical model in conformity with real strata configuration of(mainly)the Quater-nary is a prerequisite to ensure the reliability of the simulation results.In this paper,we give a detailed account ofthe technical scheme and process for creating a 3-D physical model in Kunming basin.The data used are synthe-sized from seismogeological data,borehole data,topographic data,digital elevation mode(DEM)data,seismicexploration results and wave velocity measurements.Stratigraphic division is based mainly on shear wave velocity,with strata sequence taken into consideration.The model construction is finally accomplished with ArcGIS andmany relevant programming techniques via layer-by-layer stacking(in depth direction)of the adjacent mediuminterfaces(meshes).Meanwhile,a database of 3-D physical models is set up,which provides model data and pa-rameters for strong ground motion simulation.Some processing methods and significant issues are also addressedin the paper in accordance with different types of exploration and experimental data.     

Application of a time-magnitude prediction model for earthquakes

In this paper we discuss the physical meaning of the magnitude-time model parameters for earthquake prediction. The gestation process for strong earthquake in all eleven seismic zones in China can be described by the magnitude-time prediction model using the computations of the parameters of the model. The average model parameter values for China are： b = 0.383, c=0.154, d = 0.035, B = 0.844, C = -0.209, and D = 0.188. The robustness of the model parameters is estimated from the variation in the minimum magnitude of the transformed data, the spatial extent, and the temporal period. Analysis of the spatial and temporal suitability of the model indicates that the computation unit size should be at least 4°× 4°for seismic zones in North China, at least 3° × 3° in Southwest and Northwest China, and the time period should be as long as possible.     

A study on the focal parameters of Shidian M=5.9 earthquake sequences in 2001

Introduction Comparing with the analog observation, the digital seismic observation is an advanced monitoring technique in the world, which has good points of wide band, large dynamic range, high observation precision and easy and fast analyses and processes. The Kunming Digital Seismic Network started routine observation in 1999 and now is composed of 23 digital stations all over the Yunnan Province. One of the important problems for the study of digital seismology is to de-termine the stru…     

双宽地震资料在东海X气田河道砂体预测中的应用

东海X气田主力储层埋藏深、横向变化大,常规地震资料品质较差、分辨率低,满足不了勘探开发中日益精细的地质需求。采用三船四源斜缆的采集方式获得宽频宽方位的地震资料,其具有高分辨率、高信噪比、高保真度的特征。应用宽频宽方位地震资料高分辨率、各向异性的优势信息,结合叠前同时反演,求取分方位的河道砂体敏感弹性参数反演体,并且把垂直于河道走向的多个方位反演体进行叠加,从而进行河道砂体的精细预测。相比于常规地震资料,基于宽频宽方位地震资料的储层反演提高了河道砂体的预测精度,为东海X气田的滚动勘探与开发开采奠定了基础。      

一种低成本无缆地震仪采集站的研制

随着电子技术的发展,许多新技术被应用到地球物理仪器之中.其中,无缆地震仪采集站具有重量轻、易搬运的特点,适宜应用于如森林、沼泽、沙漠等地面状况复杂的区域,可以在复杂地质条件下方便地进行地震数据采集,是未来地震仪发展的方向.本研究研发了一种低成本无缆地震仪采集站,通过分析无缆地震仪的发展方向,确定了采集站的设计方案,该系统采用了微功耗设计,GPS授时同步与低成本晶振相结合的时钟机制,并设计了基于多项分解的软件滤波器提高24位Σ-ΔADC的动态范围,其低成本、小体积、低功耗的特点使其非常适用于复杂区域下的资源勘探,并可应用于高密度、宽方位等物探新技术当中.     

大型复杂构造地震物理模型设计制作及实验精度分析(英文)

大型、构造复杂的三维物理模型可用于模拟油气勘探。构造逼近实际地质状况的模拟具有制作技术难度大、质量控制严格等特点,可用于采集宽方位、多方位和全方位的地震数据,从而进行多种三维处理、解释方法验证。本文针对中国西部前陆盆地地表条件复杂地下构造复杂,导致成像不理想等问题,基于复杂的地下构造,设计制作了目前世界上模拟施工面积最大、构造最复杂的KS(塔里木盆地克深勘探工区)物理模型。本文的模型技术的进步主要涉及3个方面:模型的设计方法、模型的浇铸流程和数据采集,首次给出了物理模型的三维真实速度模型,定量分析了物理模型的制作精度,绝对误差小于3mm,可以满足方法试验的需要。该模型基于三维形态测量技术建立了三维真实速度模型,可作为方法试验的基础数据。因此,该模型可作为地震物理模拟技术的标准。     

海试引发深水油气综合地球物理采集的几点思考

深水地球物理采集技术随着国际海洋油气勘探的不断升温,技术水平不断提高.本文结合我国的地球物理海试实践,提出深水油气综合地球物理采集的几点思考,地震采集参数的选择,重磁震采集过程的实时监控,总结海试过程深水地球物理采集的两方面进展,一是精确定位的长缆二维地震采集技术,二是高精度的重磁震联合质量监控的综合地球物理测量技术,为深水油气勘探提供采集技术保障.     

川西凹陷孝泉地区3D3C量地震资料采集方法

川西坳陷孝泉地区深层须家河组致密砂岩气藏属于典型非常规裂缝性气藏,储层识别、裂缝检测、含气性识别是气藏研究的重点和难点.转换波3D3C勘探可同时获得反映岩石骨架和各向异性特性的C波资料及反映骨架及流体特性的P波资料,因而适用于川西孝泉深层超致密裂缝性气藏.在3D3C地震勘探中,三维三分量地震采集方法是采集到高质量多分量原始资料的技术保障,本文重点研究这种采集方法.首先根据地球物理参数,结合地质任务要求,分析了三维三分量观测系统设计的方法及观测系统参数,然后根据分析结果和勘探目的层的实际情况设计了同时适合纵波勘探和转换波勘探的面元尺寸、最大和最小炮检距、接收线距、束间滚动距等参数并确定了三维三分量观测系统.该观测系统在孝泉地区资料采集中,获得的三分量资料波组特征清楚,同相轴连续,反射信息丰富;Z分量剖面和R分量剖面反射层次清楚,目的层反射特征明显,具有非常好的构造形态一致性.     

基于频率域峰值属性的河道砂体定量预测及应用(英文)

河道砂体是陆相含油气盆地最重要的储集类型之一,其边界识别和厚度定量预测是储层预测的热点难题。本文在总结现有方法技术的基础上,提出一种利用频率域峰值属性进行河道砂体边界识别和厚度定量预测的新方法。对典型河道薄砂体地震反射进行了正演模拟,构造了一种新的地震属性——峰值频率-振幅比,研究表明:峰值频率属性对地层厚度变化敏感,振幅属性对地层岩性变化敏感,两者比值突出河道砂体的边界,同时,借助峰值频率与薄层厚度间存在的定量关系进行薄砂体厚度计算。实际数据应用表明,地震峰值频率属性可以较好的刻画河道的平面展布特征;峰值频率-振幅比属性可以提高对河道砂体边界的识别能力;利用频率域地震属性进行砂体边界识别及厚度定量预测是可行的。     

三维地震勘探在城市活断层精确定位中的意义

回顾了城市活断层探测现状,指出了采用二维地震探测在活断层精确定位中存在中浅层小构造控制程度较差,在地层倾角较大地区断层归位不够准确,受建筑物和其它障碍物限制致使测线布设与断层走向斜交造成断层定位不准,以及由于测网密度限制造成的断层交汇处、断层分段点、端点位置控制程度较差等主要问题．从理论上分析了三维地震勘探的优势,认为三维地震勘探可以较好地解决由于二维地震勘探本身的技术缺陷和地表环境、地质条件影响所造成的断层定位不准的问题．通过实例剖析,从野外采集难点, 仪器选择, 观测系统定义, 优化施工设计, 野外质量监控, 特殊数据处理手段, 以及取得的良好地质效果等方面进行详细阐述,论证了利用三维地震探测在城市进行活断层精确定位中的可行性及其意义．      

“宽频带、宽方位和高密度”陆上三维地震观测系统聚焦分辨率分析

近年来,"两宽一高"——宽频带、宽方位和高密度——三维地震采集技术极大地提升了地震勘探的能力和精度,在岩性油气藏地区取得了明显的应用效果,也对地震采集观测系统设计提出了更高的要求.如何在现有的成本限制和装备条件下,根据具体工区的地质地球物理条件来选择合适的"两宽一高"采集观测参数以实现最佳的勘探效益,已成为当前地震勘探中迫切需要解决的瓶颈问题之一.基于此,本文首先回顾了点绕射聚焦分析的基本原理,随后给出一种新的复杂介质多频率快速聚焦分辨率定量分析方法.基于该理论,我们以一个典型的陆上三维地震勘探采集方案和速度模型为例,系统地研究了"两宽一高"地震资料偏移成像分辨率随着关键采集参数的变化规律,给出了不同条件下分辨率的理论极限值及其所对应的采集参数的临界点值.此外,我们也提出了一种新的采集参数和子波频谱的交汇定量分析方法,进一步阐明了采集参数和子波频谱参数之间的定量关系,为复杂接收激发条件下采集观测系统设计提供了新的理论依据.     

用于陆上宽频地震采集的设备及应用实例

宽频带、宽方位、高密度地震数据采集是近年地震勘探的重要发展方向,随着现代电子设备的可靠性大幅度提高,使得"两宽一高"采集技术得以推广应用。本文重点介绍陆上地震采集可控震源设备(Nomad系列)和数字检波器(DSU1-508)针对采集需求所做的技术改进,如何在保证生产效率、降低采集成本的前提下,使高密度采集成为可能,并满足深层勘探和高精度勘探的需求。通过分析高密度采集数据的处理结果并与常规采集效果进行对比,结果表明新一代设备在拓宽频带,提高分辨率的同时,极大地改善了成像质量。     

Application of 3D vertical seismic profile multi‐component data to tight gas sands‡

Due to the complicated geophysical character of tight gas sands in the Sulige gasfield of China, conventional surface seismic has faced great challenges in reservoir delineation. In order to improve this situation, a large‐scale 3D‐3C vertical seismic profiling (VSP) survey (more than 15 000 shots) was conducted simultaneously with 3D‐3C surface seismic data acquisition in this area in 2005. This paper presents a case study on the delineation of tight gas sands by use of multi‐component 3D VSP technology. Two imaging volumes (PP compressional wave; PSv converted wave) were generated with 3D‐3C VSP data processing. By comparison, the dominant frequencies of the 3D VSP images were 10–15 Hz higher than that of surface seismic images. Delineation of the tight gas sands is achieved by using the multi‐component information in the VSP data leading to reduce uncertainties in data interpretation. We performed a routine data interpretation on these images and developed a new attribute titled ‘Centroid Frequency Ratio of PSv and PP Waves’ for indication of the tight gas sands. The results demonstrated that the new attribute was sensitive to this type of reservoir. By combining geologic, drilling and log data, a comprehensive evaluation based on the 3D VSP data was conducted and a new well location for drilling was proposed. The major results in this paper tell us that successful application of 3D‐3C VSP technologies are only accomplished through a synthesis of many disciplines. We need detailed analysis to evaluate each step in planning, acquisition, processing and interpretation to achieve our objectives. High resolution, successful processing of multi‐component information, combination of PP and PSv volumes to extract useful attributes, receiver depth information and offset/ azimuth‐dependent anisotropy in the 3D VSP data are the major accomplishments derived from our attention to detail in the above steps.