WO2020087767A1 - 基于台站与三维地震联合采集资料的速度反演方法 - Google Patents

基于台站与三维地震联合采集资料的速度反演方法 Download PDF

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WO2020087767A1
WO2020087767A1 PCT/CN2019/000145 CN2019000145W WO2020087767A1 WO 2020087767 A1 WO2020087767 A1 WO 2020087767A1 CN 2019000145 W CN2019000145 W CN 2019000145W WO 2020087767 A1 WO2020087767 A1 WO 2020087767A1
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station
data
inversion
seismic
velocity
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尚新民
芮拥军
崔庆辉
赵胜天
刁瑞
冮明川
隋旭强
王蓬
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China Petroleum and Chemical Corp
Sinopec Shengli Geological Scientific Reserch Institute
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China Petroleum and Chemical Corp
Sinopec Shengli Geological Scientific Reserch Institute
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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01VGEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V1/00Seismology; Seismic or acoustic prospecting or detecting
    • G01V1/28Processing seismic data, e.g. for interpretation or for event detection

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  • the invention relates to the field of oil and gas seismic exploration, in particular to a speed inversion method based on the joint acquisition of data by a station and a three-dimensional earthquake.
  • Hua Biaolong deduced the formula for the partial derivative of the interface suitable for the reflection and transmission of seismic waves in two-dimensional layered media, and applied it to the joint inversion of interface and velocity in two-dimensional layered media. play.
  • McCaughey used transmission waves, wide-angle reflection and refraction travel to simultaneously invert the velocity and interface depth. This method stabilized the inversion by weighing the values of different dimensions in the coefficient matrix and adding regularization to the inversion Solution.
  • Zhang Jie proposed a non-linear refraction and reflection wave travel time inversion method, this method uses the refraction and reflection waves travel at the same time inversion.
  • the object of the present invention is to provide a speed inversion method based on the joint acquisition of data from stations and three-dimensional earthquakes that can effectively improve the accuracy of deep layer velocity modeling.
  • a velocity inversion method based on the joint acquisition of data by the station and the 3D earthquake includes: Step 1: According to the 3D earthquake Observation system, combined with the actual surface conditions, lay out stations before the 3D seismic construction, and record continuously; Step 2: Match the station and the 3D seismic coordinate system to unify the coordinates of the two observation systems; Step 3: From continuous In the recorded station data, intercept the data within the shooting period; Step 4: Match the intercepted station record data with the three-dimensional seismic record data to synchronize the two data in time; Step 5: Match Pick up the first arrival time on the later station data; Step 6: Pick up the reflected arrival time on the 3D seismic data; Step 7: Establish the underground initial velocity model; Step 8: Use the picked station first arrival time Perform multi-scale joint tomographic inversion with 3D seismic reflection travel time; Step 9: When the inversion results converge, output the results as
  • the object of the present invention can also be achieved by the following technical measures:
  • step 1 the layout of the station uses a parallel staggered pattern.
  • step 1 the station used can record continuously for at least 4 days, the collected data is automatically stored on the memory card carried by itself, and it can continue to work after replacing the backup battery.
  • step 1 the station adopts the method of digging and burying to ensure that the station is at least 60cm away from the surface.
  • step 2 the coordinate matching method of the two observation systems is to use the coordinates of the detector at the point where the station and the detector coincide to obtain the coordinates of the unknown station, and to obtain the coordinates of the station that are consistent with the coordinates of the detector by solving the following equations :
  • (x, y) is the coordinates of the station to be sought
  • (x 1 , y 1 ), (x 2 , y 2 ), (x 3 , y 3 ) are the coordinates of the three stations near the station to be sought
  • D 1 , d 2 , and d 3 are the distances from the station to the nearby three stations, and the distance is calculated by the coordinates measured by the handheld GPS device.
  • step 3 intercept the data in the shooting time period from the continuously recorded station data, first sample and calculate the approximate time difference between the station timing system and the 3D seismic timing system, and then shoot each field shot in the 3D seismic field The time is the center, and the data within the time difference is intercepted before and after the output.
  • step 4 before matching the intercepted station record data with the three-dimensional seismic record data, it is necessary to match the two recorded waveforms to keep the two recorded waveforms as consistent as possible.
  • step 4 before matching the intercepted station record data with the three-dimensional seismic record data, it is necessary to filter and normalize the two records after waveform matching.
  • step 4 the intercepted station record data is matched with the three-dimensional seismic record data by calculating the corresponding cross-correlation overlay value of the two records, and determining the accurate firing time on the station data by the maximum cross-correlation overlay value. And intercept the output station data according to the set data length.
  • step 5 the first arrival pick-up on the station data is completed in the co-detection point data set of the station data, which is to extract the data from the common-shot point station into the co-detection point station data, and follow the deviation
  • the shift distance is rearranged, and then the first arrival is automatically picked up using the energy ratio method of long and short time windows.
  • step 6 the pick-up of the reflected wave arrival time on the 3D seismic data is done on the common shot point data set.
  • the reflection in-phase axis with high signal-to-noise is selected as the standard reflection layer, which is performed automatically and manually. Pick up when the reflected wave arrives.
  • the initial velocity model is a layered velocity model obtained by multiscale grid tomographic inversion of the first arrival travel time of the station data.
  • the process is to discretize the actual geological model with grids of different sizes. Invert each scale model.
  • step 8 the joint tomographic inversion of the first arrival travel time of the station and the 3D seismic reflection travel time is to discretize the underground velocity structure into a layered model, and to invert the fluctuations of the velocity interface and the velocity values within the layer.
  • step 8 the joint inversion of the first arrival wave travel time of the station and the three-dimensional seismic reflection wave travel time is to calculate the perturbation amount of the change of the node position on each scale after multi-scale decomposition of the interface to the arrival time of the seismic wave, and use Inversion speed model of reflected wave travel time.
  • step 8 the joint inversion of the first arrival travel time of the station and the three-dimensional seismic reflection travel time is to discretize the actual geological model with grids of different sizes, and invert the models at various scales simultaneously during the inversion process.
  • step 8 in the joint tomographic inversion equation of the station's first arrival travel time and 3D seismic reflected wave travel time, both the first arrival wave and the reflected wave arrival time are used to invert the velocity model.
  • the speed inversion method based on the joint acquisition of data by stations and 3D earthquakes in the present invention changes the method of using a single observation system for conventional 3D earthquakes, and obtains a large offset by deploying sparse stations without substantially increasing the acquisition cost
  • the first arrival wave information, combined with the three-dimensional seismic reflection information, to perform the first tomographic and reflected wave tomographic inversion can effectively improve the accuracy of deep velocity modeling.
  • Using this method can reduce the multiple solutions of deep velocity inversion, improve the accuracy of deep velocity inversion, and improve the imaging quality of deep seismic data.
  • Figure 1 is a schematic diagram of the theoretical layered velocity model and ray tracing results of the Shengli oilfield A;
  • Figure 2 is a schematic diagram of the results of the first arrival wave inversion in the Shengli Oilfield Engineering Area
  • Figure 3 is a schematic diagram of the results of inversion of reflected wave A in the Shengli Oilfield Engineering Area
  • Figure 4 is a schematic diagram of the results of the joint inversion of the first arrival wave and reflected wave in the Shengli Oilfield Engineering Area;
  • 5 is a three-dimensional seismic observation system diagram of the location (triangle) of the sparse station B in the Shengli Oilfield Engineering Area;
  • Figure 6 is a schematic diagram of a section of station data (common shot data set) intercepted by B of Shengli Oilfield;
  • FIG. 7 is a schematic diagram showing the offset of the common station data set after the matching of Shengli Oilfield Engineering Area B is completed;
  • FIG. 8 is a schematic diagram of the multi-scale joint tomographic inversion result of the first arrival wave and the reflected wave of a certain survey line of Shengli Oilfield Engineering Area B;
  • FIG. 9 is a flowchart of a specific embodiment of a speed inversion method based on combined data acquisition of a station and a three-dimensional earthquake according to the present invention.
  • FIG. 9 is a flowchart of the velocity inversion method based on the station and three-dimensional seismic joint acquisition data of the present invention.
  • Step 101 According to the 3D seismic observation system, combined with the actual surface conditions, the stations are laid out before the 3D seismic construction, and continuous recording is made; the layout of the stations adopts a parallel staggered pattern.
  • the station used can record continuously for at least 4 days, the collected data can be automatically stored on the memory card carried by itself, and can continue to work after replacing the backup battery.
  • the station adopts the method of digging and burying to ensure that the station is at least 60cm away from the surface.
  • Step 102 Match the station and the three-dimensional seismic coordinate system to unify the coordinates of the two observation systems; the coordinate matching method of the two observation systems is to use the detector coordinates of the point where the station and the detector coincide to obtain the unknown station
  • the coordinates can be obtained by solving the following equations to obtain the coordinates of the station that are consistent with the coordinates of the geophone:
  • (x, y) is the coordinates of the station to be sought
  • (x 1 , y 1 ), (x 2 , y 2 ), (x 3 , y 3 ) are the coordinates of the three stations near the station to be sought
  • D 1 , d 2 , and d 3 are the distances from the station to the nearby three stations, and the distance is calculated by the coordinates measured by the handheld GPS device.
  • Step 103 Intercept the data in the blasting period from the continuously recorded station data; intercept the data in the blasting period from the continuously recorded station data, first sample the statistics of the station timing system and the three-dimensional seismic timing system Time difference range, then take the field shooting time of each shot recorded by the 3D seismic as the center, and intercept the data within the time difference range before and after output.
  • Step 104 Match the intercepted station record data with the 3D seismic record data to synchronize the two data in time; before matching the intercepted station record data with the 3D seismic record data, two The matching of the recorded waveforms makes the two recorded waveforms as consistent as possible. Before matching the intercepted station record data with the three-dimensional seismic record data, it is necessary to filter and normalize the two records after waveform matching.
  • the intercepted station record data is matched with the three-dimensional seismic record data by calculating the corresponding cross-correlation superposition value of the two types of records, and determining the accurate shooting time on the station data by the maximum cross-correlation superposition value, and according to the set The data length intercepts the output station data.
  • Step 105 Picking the first arrival arrival time on the matched station data; picking the first arrival arrival time on the station data is completed in the common detection point data set of the station data, which is about to fire the station
  • the station data is extracted into common detection station data, and rearranged according to the distance of the offset, and then the first arrival is automatically picked up using the energy ratio method of long and short time windows.
  • Step 106 Picking up the reflected wave arrival time on the 3D seismic data; picking up the reflected wave arrival time on the 3D seismic data is done in the common shot data set, and selecting the reflection in-phase axis with higher signal-to-noise as the standard when picking up
  • the reflective layer picks up the arrival of the reflected wave in an automatic and manual manner.
  • Step 107 Use the first arrival wave multi-scale tomographic inversion results to establish an underground layered initial velocity model; use the first arrival wave travel time of the station data, perform a multi-scale grid tomographic inversion, and use the inversion results to establish the layered initial velocity model.
  • Step 108 Use the tomographic inversion of the first arrival travel time of the station and the 3D seismic reflected wave travel time; the tomographic inversion of the first arrival wave travel time of the station and the 3D seismic reflection wave travel time is to discretize the underground velocity structure as Layered model, inversion of velocity interface fluctuations and velocity values in layers.
  • the amount of perturbation of the seismic wave arrival time at each scale after the multi-scale decomposition of the interface is calculated, and the first arrival wave and the reflected wave travel time are used at the same time. Inversion speed model.
  • the actual geological model is discretized with grids of different sizes (scales), and the inversion of each scale model is simultaneously performed during the inversion process.
  • Step 109 When the inversion result converges, the result is output as the final inversion speed model.
  • Example 1 is derived from the inversion result of a theoretical velocity model of Sinopec Shengli Oilfield. The effectiveness of the method can be verified through this example.
  • the specific implementation is:
  • Example 2 is derived from the joint acquisition project of a station and three-dimensional earthquake in Shengli Oilfield of Sinopec.
  • the specific implementation mode is:

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Abstract

一种基于台站与三维地震联合采集资料的速度反演方法,该基于台站与三维地震联合采集资料的速度反演方法包括台站布设位置设计(101)、台站与三维地震数据联合采集、台站与三维地震观测系统坐标匹配(102)、台站数据截取(103)、台站与三维地震数据匹配(104)、台站初至波走时拾取(105)、三维地震反射波走时拾取(106)、初始速度模型建立(107)、初至波与反射波走时联合反演(108)、速度模型输出(109)。该基于台站与三维地震联合采集资料的速度反演方法可以减少深层速度反演的多解性,提高深层速度反演的精度,改善深层地震资料的成像质量。

Description

基于台站与三维地震联合采集资料的速度反演方法 技术领域
本发明涉及油气地震勘探领域,特别是涉及到一种基于台站与三维地震联合采集资料的速度反演方法。
背景技术
自从在亚特兰大召开的第54届地球物理勘探学家协会年会上设置了地震速度成像研究内容的专题之后,经过以Daily,Somerstein,Bishop,Dyer和Worthington等人为代表的大量研究,地震波速度反演的理论、方法和技术以数值模拟得以迅速的发展。就多种波旅行时联合速度反演这一重要分支而言,其发展现状如下:1992年,Zelt提出了一种基于任意类型的地震体波的同时确定二维地壳的速度及界面形态的地震旅行时反演方法。1995年,华标龙推导出了二维层状介质中适用于反射波和透射波的地震波旅行时对界面偏导数的公式,并将其用于二维层状介质中界面和速度的联合反演。1997年,McCaughey利用透射波、广角反射以及折射旅行时来同时反演速度和界面深度,该方法通过对系数矩阵内不同量纲的值加以权衡值,并在反演中加入正则化来稳定反演的解。1998年,Zhang Jie提出了一种非线性折射波和反射波旅行时反演方法,该方法利用折射波和反射波旅行时同时进行速度反演。2003年,James利用透射、广角反射、折射以及多次波旅行时对三维速度及界面进行同时速度,在反演过程中使数据误差和模型粗糙度趋向于最小来寻找一个合适的层速度一界面模型。2003年,Zhou提出了基于反演界面形态的可变形层析成像方法。由于绝大多数沉积盆地都具有层状速度结构,解决当前基于网格和节点参数化的层析方法难以高精度重构层状速度结构的问题。2006年,Zhou在模型参数化时,又引入多尺度参数化,发展出初至多尺度可变形层析成像方法和反射尺度可变形层析成像方法,与单尺度层析相比,多尺度层析反演结果更加稳定可靠。2006年,周龙泉依据波逆行原理推导了三维层状介质中地震波旅行时对界面偏导数的公式,得到了复杂界面情况下,反演时所需的旅行时对界面偏导数系数矩阵,通过模型试算,证实了该方法对三维速度结构和界面重构是有效的。2011年,白超英等人将不同震相种类数据的权系数以及不同种类参数的归一化因子引 入到反演算法之中,实现了三维复杂层状介质中多震相走时联合反演成像。
关于多震相联合反演问题的研究由来已久,但是面对的都是盆地规模的宏观速度反演问题,而且现有的技术都是基于同一种观测系统和同一种检波器,解决的是速度反演精度的问题。如何利用好初至波和反射波各自优点提高油气田深层速度模型反演的精度,未见公开发表的技术成果,这是因为受限于经济成本和施工可行性,现有的油气地震勘探观测系统的最大偏移距受到了限制,无法接收到来自深层的地震波信息。
胜利油田近几年深层油气储量显著增长,石油与天然气地质储量丰富,但整体勘探程度较低,存在构造落实难、有效储层描述困难等问题。二次采集的高精度三维资料虽然大幅度提高了深层地震资料的成像质量,但对于地质和油藏描述要求,还存在一定的多解性,主要矛盾就是深层速度模型精度的问题。为此我们发明了一种新的基于台站与三维地震联合采集资料的速度反演方法,解决了以上技术问题。
发明内容
本发明的目的是提供一种能够有效提高深层速度建模精度的基于台站与三维地震联合采集资料的速度反演方法。
本发明的目的可通过如下技术措施来实现:基于台站与三维地震联合采集资料的速度反演方法,该基于台站与三维地震联合采集资料的速度反演方法包括:步骤1:根据三维地震观测系统,结合实际地表情况,在三维地震施工前布设好台站,进行连续记录;步骤2:对台站和三维地震坐标系统进行匹配,使两种观测系统的坐标统一;步骤3:从连续记录的台站数据中,截取放炮时间段内的数据;步骤4:将截取的台站记录数据与三维地震记录的数据进行匹配,使两种数据做到时间上的同步;步骤5:在匹配后的台站数据上进行初至波到时拾取;步骤6:在三维地震数据上进行反射波到时拾取;步骤7:建立地下初始速度模型;步骤8:利用拾取的台站初至波走时和三维地震反射波走时进行多尺度联合层析反演;步骤9:当反演结果收敛时,将结果输出作为最终反演的速度模型。
本发明的目的还可通过如下技术措施来实现:
在步骤1中,台站的布设采用的是平行交错式图形。
在步骤1中,采用的台站可连续记录至少4天,采集的数据自动存储在自 身携带的存储卡上,更换备用电池后可继续工作。
在步骤1中,台站采用挖坑掩埋的方法,保证台站距地表最少60cm。
在步骤2中,两种观测系统的坐标匹配方法是利用台站与检波器重合点的检波器坐标求取未知的台站坐标,通过求解如下方程组求取与检波器坐标一致的台站坐标:
Figure PCTCN2019000145-appb-000001
其中,(x,y)为待求台站的坐标,(x 1,y 1)、(x 2,y 2)、(x 3,y 3)为待求台站附近三个台站的坐标,d 1、d 2、d 3分别为待求台站到附近三个台站的距离,该距离通过手持GPS设备测量的坐标计算得到。
在步骤3中,从连续记录的台站数据中截取放炮时间段内的数据,首先抽样统计台站计时系统与三维地震计时系统的大概时差范围,然后以三维地震记录的每一炮的野外放炮时间为中心,前后截取时差范围内的数据输出。
在步骤4中,将截取的台站记录数据与三维地震记录的数据进行匹配前,需要进行两种记录波形的匹配,使两种记录的波形尽量保持一致。
在步骤4中,将截取的台站记录数据与三维地震记录的数据进行匹配前,需要对波形匹配后的两种记录进行滤波和归一化处理。
在步骤4中,将截取的台站记录数据与三维地震记录的数据进行匹配,是通过计算对应的两种记录互相关叠加值,通过最大互相关叠加值确定台站数据上准确的放炮时刻,并按照设定的数据长度截取输出台站数据。
在步骤5中,台站数据上进行初至波到时拾取是在台站数据的共检波点数据集内完成的,即将共炮点台站数据抽取成共检波点台站数据,并按照偏移距远近重新排列,然后利用长短时窗能量比方法自动拾取初至。
在步骤6中,在三维地震数据上进行反射波到时拾取是在共炮点数据集完成的,拾取时选择信噪比较高的反射同相轴作为标准反射层,通过自动和人工的方式进行反射波到时拾取。
在步骤7中,初始速度模型是利用台站数据的初至波走时进行多尺度网格层析反演得到的层状速度模型,其过程是以不同大小的网格离散化实际地 质模型,同时对各个尺度模型进行反演。
在步骤8中,台站初至波走时和三维地震反射波走时联合层析反演,是将地下速度结构离散为层状模型,反演速度界面的起伏和层内的速度值。
在步骤8中,台站初至波走时和三维地震反射波走时联合反演,是通过计算界面多尺度分解后各个尺度上的节点位置变化对地震波到时的扰动量,同时使用初至波和反射波走时反演速度模型。
在步骤8中,台站初至波走时和三维地震反射波走时联合反演,是以不同大小的网格离散化实际地质模型,在反演过程中同时对各个尺度模型进行反演。
在步骤8中,台站初至波走时和三维地震反射波走时联合层析反演方程中,同时使用了初至波和反射波到时进行速度模型的反演。
本发明中的基于台站与三维地震联合采集资料的速度反演方法,改变了常规三维地震采用单一观测系统的方法,在基本不增加采集成本的条件下,通过布设稀疏台站获得超大偏移距初至波信息,结合三维地震反射信息进行初至波与反射波联合层析反演,能够有效提高深层速度建模精度。利用该方法可以减少深层速度反演的多解性,提高深层速度反演的精度,改善深层地震资料的成像质量。
附图说明
图1是胜利油田工区A理论层状速度模型及射线追踪结果的示意图;
图2是胜利油田工区A初至波反演结果的示意图;
图3是胜利油田工区A反射波反演结果的示意图;
图4是胜利油田工区A初至波与反射波联合反演结果的示意图;
图5是胜利油田工区B稀疏台站位置(三角形)、三维地震观测系统图;
图6是胜利油田工区B截取的一段台站数据(共炮点数据集)的示意图;
图7是胜利油田工区B匹配完成后的共台站数据集按偏移距显示的示意图;
图8是胜利油田工区B某一条测线初至波与反射波多尺度联合层析反演结果的示意图;
图9为本发明的基于台站与三维地震联合采集资料的速度反演方法的一具体实施例的流程图。
具体实施方式
为使本发明的上述和其他目的、特征和优点能更明显易懂,下文特举出较佳实施例,并配合附图所示,作详细说明如下。
如图9所示,图9为本发明的基于台站与三维地震联合采集资料的速度反演方法的流程图。
步骤101:根据三维地震观测系统,结合实际地表情况,在三维地震施工前布设好台站,进行连续记录;台站的布设采用的是平行交错式图形。采用的台站可连续记录至少4天,采集的数据可自动存储在自身携带的存储卡上,更换备用电池后可继续工作。台站采用挖坑掩埋的方法,保证台站距地表最少60cm。
步骤102:对台站和三维地震坐标系统进行匹配,使两种观测系统的坐标统一;两种观测系统的坐标匹配方法是利用台站与检波器重合点的检波器坐标求取未知的台站坐标,可通过求解如下方程组求取与检波器坐标一致的台站坐标:
Figure PCTCN2019000145-appb-000002
其中,(x,y)为待求台站的坐标,(x 1,y 1)、(x 2,y 2)、(x 3,y 3)为待求台站附近三个台站的坐标,d 1、d 2、d 3分别为待求台站到附近三个台站的距离,该距离通过手持GPS设备测量的坐标计算得到。
步骤103:从连续记录的台站数据中,截取放炮时间段内的数据;从连续记录的台站数据中截取放炮时间段内的数据,首先抽样统计台站计时系统与三维地震计时系统的大概时差范围,然后以三维地震记录的每一炮的野外放炮时间为中心,前后截取时差范围内的数据输出。
步骤104:将截取的台站记录数据与三维地震记录的数据进行匹配,使两种数据做到时间上的同步;将截取的台站记录数据与三维地震记录的数据进行匹配前,需要进行两种记录波形的匹配,使两种记录的波形尽量保持一致。将截取的台站记录数据与三维地震记录的数据进行匹配前,需要对波形匹配后的两种记录进行滤波和归一化处理。将截取的台站记录数据与三维地 震记录的数据进行匹配,是通过计算对应的两种记录互相关叠加值,通过最大互相关叠加值确定台站数据上准确的放炮时刻,并按照设定的数据长度截取输出台站数据。
步骤105:在匹配后的台站数据上进行初至波到时拾取;台站数据上进行初至波到时拾取是在台站数据的共检波点数据集内完成的,即将共炮点台站数据抽取成共检波点台站数据,并按照偏移距远近重新排列,然后利用长短时窗能量比方法自动拾取初至。
步骤106:在三维地震数据上进行反射波到时拾取;在三维地震数据上进行反射波到时拾取是在共炮点数据集完成的,拾取时选择信噪比较高的反射同相轴作为标准反射层,通过自动和人工的方式进行反射波到时拾取。
步骤107:利用初至波多尺度层析反演结果建立地下层状初始速度模型;使用台站数据的初至波走时,进行多尺度网格层析反演,利用反演结果建立层状初始速度模型。
步骤108:利用拾取的台站初至波走时和三维地震反射波走时进行联合层析反演;台站初至波走时和三维地震反射波走时联合层析反演,是将地下速度结构离散为层状模型,反演速度界面的起伏和层内的速度值。台站初至波走时和三维地震反射波走时联合层析反演中,通过计算界面多尺度分解后各个尺度上的节点位置变化对地震波到时的扰动量,同时使用初至波和反射波走时反演速度模型。台站初至波走时和三维地震反射波走时联合层析反演方程中,以不同大小(尺度)的网格离散化实际地质模型,在反演过程中同时对各个尺度模型进行反演。
步骤109:当反演结果收敛时,将结果输出作为最终反演的速度模型。
以下为应用本发明的具体实施例,实施例1来源于中石化胜利油田一个理论速度模型的反演结果,通过该实施例可验证方法的有效性,具体实施方式为:
(1)根据工区地震资料解释成果,建立二维层状速度模型,如图1所示;
(2)利用射线追踪计算得到初至波与反射波走时,图1中的灰色折线为初至波射线追踪结果,图1中黑色折线为反射波射线追踪结果;
(3)只利用初至波走时反演速度模型,结果如图2,结果与真实速度模型相差较大;
(4)只利用反射波走时反演速度模型,结果如图3,结果优于单独利用初至波反演;
(5)利用初至波与反射波走时进行联合层析反演,结果如图4,联合反演结果明显优于单独的初至波或反射波反演结果。
实施例2来源于中石化胜利油田一个台站与三维地震联合采集项目,具体实施方式为:
(1)根据三维地震观测系统,结合实际地表情况,在三维地震施工前布设好台站,进行连续记录,台站位置与三维地震观测系统如图5所示。
(2)对台站和三维地震坐标系统进行匹配,使两种观测系统的坐标统一。
(3)从连续记录的台站数据中,截取放炮时间段内的数据,图6为截取的某一炮的台站数据。
(4)将截取的台站记录数据与三维地震记录的数据进行匹配,使两种数据做到时间上的同步,图7为匹配完成后的某一台站的共台站数据集按偏移距显示结果。
(5)在匹配后的台站数据上进行初至波到时拾取。
(6)在三维地震数据上进行反射波到时拾取。
(7)利用初至波多尺度网格层析反演结果建立地下层状初始速度模型。
(8)利用拾取的台站初至波走时和三维地震反射波走时进行联合层析反演,图8为台站初至走时与三维地震反射走时联合层析反演结果。
(9)当反演结果收敛时,将结果输出作为最终反演的速度模型。

Claims (16)

  1. 基于台站与三维地震联合采集资料的速度反演方法,其特征在于,该基于台站与三维地震联合采集资料的速度反演方法包括:
    步骤1:根据三维地震观测系统,结合实际地表情况,在三维地震施工前布设好台站,进行连续记录;
    步骤2:对台站和三维地震坐标系统进行匹配,使两种观测系统的坐标统一;
    步骤3:从连续记录的台站数据中,截取放炮时间段内的数据;
    步骤4:将截取的台站记录数据与三维地震记录的数据进行匹配,使两种数据做到时间上的同步;
    步骤5:在匹配后的台站数据上进行初至波到时拾取;
    步骤6:在三维地震数据上进行反射波到时拾取;
    步骤7:建立地下初始速度模型;
    步骤8:利用拾取的台站初至波走时和三维地震反射波走时进行多尺度联合层析反演;
    步骤9:当反演结果收敛时,将结果输出作为最终反演的速度模型。
  2. 根据权利要求1所述的基于台站与三维地震联合采集资料的速度反演方法,其特征在于,在步骤1中,台站的布设采用的是平行交错式图形。
  3. 根据权利要求1所述的基于台站与三维地震联合采集资料的速度反演方法,其特征在于,在步骤1中,采用的台站可连续记录至少4天,采集的数据自动存储在自身携带的存储卡上,更换备用电池后可继续工作。
  4. 根据权利要求1所述的基于台站与三维地震联合采集资料的速度反演方法,其特征在于,在步骤1中,台站采用挖坑掩埋的方法,保证台站距地表最少60cm。
  5. 根据权利要求1所述的基于台站与三维地震联合采集资料的速度反演方法,其特征在于,在步骤2中,两种观测系统的坐标匹配方法是利用台站与检波器重合点的检波器坐标求取未知的台站坐标,通过求解如下方程组求取与检波器坐标一致的台站坐标:
    Figure PCTCN2019000145-appb-100001
    其中,(x,y)为待求台站的坐标,(x 1,y 1)、(x 2,y 2)、(x 3,y 3)为待求台站附近三个台站的坐标,d 1、d 2、d 3分别为待求台站到附近三个台站的距离,该距离通过手持GPS设备测量的坐标计算得到。
  6. 根据权利要求1所述的基于台站与三维地震联合采集资料的速度反演方法,其特征在于,在步骤3中,从连续记录的台站数据中截取放炮时间段内的数据,首先抽样统计台站计时系统与三维地震计时系统的大概时差范围,然后以三维地震记录的每一炮的野外放炮时间为中心,前后截取时差范围内的数据输出。
  7. 根据权利要求1所述的基于台站与三维地震联合采集资料的速度反演方法,其特征在于,在步骤4中,将截取的台站记录数据与三维地震记录的数据进行匹配前,需要进行两种记录波形的匹配,使两种记录的波形尽量保持一致。
  8. 根据权利要求1所述的基于台站与三维地震联合采集资料的速度反演方法,其特征在于,在步骤4中,将截取的台站记录数据与三维地震记录的数据进行匹配前,需要对波形匹配后的两种记录进行滤波和归一化处理。
  9. 根据权利要求1所述的基于台站与三维地震联合采集资料的速度反演方法,其特征在于,在步骤4中,将截取的台站记录数据与三维地震记录的数据进行匹配,是通过计算对应的两种记录互相关叠加值,通过最大互相关叠加值确定台站数据上准确的放炮时刻,并按照设定的数据长度截取输出台站数据。
  10. 根据权利要求1所述的基于台站与三维地震联合采集资料的速度反演方法,其特征在于,在步骤5中,台站数据上进行初至波到时拾取是在台站数据的共检波点数据集内完成的,即将共炮点台站数据抽取成共检波点台站数据,并按照偏移距远近重新排列,然后利用长短时窗能量比方法自动拾取初至。
  11. 根据权利要求1所述的基于台站与三维地震联合采集资料的速度反 演方法,其特征在于,在步骤6中,在三维地震数据上进行反射波到时拾取是在共炮点数据集完成的,拾取时选择信噪比较高的反射同相轴作为标准反射层,通过自动和人工的方式进行反射波到时拾取。
  12. 根据权利要求1所述的基于台站与三维地震联合采集资料的速度反演方法,其特征在于,在步骤7中,初始速度模型是利用台站数据的初至波走时进行多尺度网格层析反演得到的层状速度模型,其过程是以不同大小的网格离散化实际地质模型,同时对各个尺度模型进行反演。
  13. 根据权利要求1所述的基于台站与三维地震联合采集资料的速度反演方法,其特征在于,在步骤8中,台站初至波走时和三维地震反射波走时联合层析反演,是将地下速度结构离散为层状模型,反演速度界面的起伏和层内的速度值。
  14. 根据权利要求1所述的基于台站与三维地震联合采集资料的速度反演方法,其特征在于,在步骤8中,台站初至波走时和三维地震反射波走时联合反演,是通过计算界面多尺度分解后各个尺度上的节点位置变化对地震波到时的扰动量,同时使用初至波和反射波走时反演速度模型。
  15. 根据权利要求1所述的基于台站与三维地震联合采集资料的速度反演方法,其特征在于,在步骤8中,台站初至波走时和三维地震反射波走时联合反演,是以不同大小的网格离散化实际地质模型,在反演过程中同时对各个尺度模型进行反演。
  16. 根据权利要求1所述的基于台站与三维地震联合采集资料的速度反演方法,其特征在于,在步骤8中,台站初至波走时和三维地震反射波走时联合层析反演方程中,同时使用了初至波和反射波到时进行速度模型的反演。
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