CN117826256A - Method and device for determining sequence boundary of high-frequency seismic sequence stratum - Google Patents

Method and device for determining sequence boundary of high-frequency seismic sequence stratum Download PDF

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CN117826256A
CN117826256A CN202311734898.0A CN202311734898A CN117826256A CN 117826256 A CN117826256 A CN 117826256A CN 202311734898 A CN202311734898 A CN 202311734898A CN 117826256 A CN117826256 A CN 117826256A
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curve
sequence boundary
frequency
earthquake
sequence
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徐宁
郭同翠
赵俊峰
徐振永
刘会峰
谢伟
宋敏
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China Petroleum Dubai Research Institute
Petrochina Co Ltd
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Petrochina Co Ltd
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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
    • G01V1/30Analysis
    • G01V1/306Analysis for determining physical properties of the subsurface, e.g. impedance, porosity or attenuation profiles
    • 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
    • G01V1/282Application of seismic models, synthetic seismograms

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Abstract

The invention discloses a method and a device for determining an interval boundary of a high-frequency earthquake interval stratum, wherein the method comprises the following steps: according to the three-dimensional seismic data volume, a relative geologic time model is generated, an initial medium-low frequency first sequence boundary data volume based on the earthquake is extracted, a medium-low frequency first sequence boundary curve based on the earthquake is extracted, baseline removal processing is carried out, a second sequence boundary data volume based on the earthquake is obtained through first waveform difference inversion, a third sequence boundary curve based on the earthquake is extracted and used as a basic curve, and is fused with a gamma curve, a porosity curve, a carbonate particle curve and a carbonate texture curve which reflect high-frequency sequence boundaries, a carbonate suture line frequency curve, an asphalt content curve and a dolomite content curve which reflect the sequence boundaries, a Gao Pindi sequence boundary data volume based on the earthquake is obtained after second waveform difference inversion, and the high-frequency earthquake sequence boundary is identified.

Description

高频地震层序地层的层序边界确定方法及装置Method and device for determining sequence boundaries of high-frequency seismic sequence stratigraphy

技术领域Technical Field

本发明涉及碳酸盐岩地层油气勘探开发,以及地层高频海平面变化旋回层序体的地震方面划分技术领域,尤其涉及一种高频地震层序地层的层序边界确定方法及装置。The present invention relates to the field of carbonate stratum oil and gas exploration and development, and the technical field of seismic division of high-frequency sea level change cyclic sequence bodies, and in particular to a method and device for determining the sequence boundary of high-frequency seismic sequence strata.

背景技术Background technique

本部分旨在为权利要求书中陈述的本发明实施例提供背景或上下文。此处的描述不因为包括在本部分中就承认是现有技术。This section is intended to provide a background or context to the embodiments of the invention recited in the claims. No description herein is admitted to be prior art by inclusion in this section.

地层单元包含一个完整的基准面旋回期间在所有成因上有联系的沉积环境中沉积的地层。一个成因层序的半旋回边界发生在基准面上升到下降或者在下降到上升的转换位置。在不同的古地理环境,这些转换点或表现为地层不连续面,或表现为分别记录了可容纳空间增加或减小的整合地层,通常形成层序界面。A stratigraphic unit consists of strata deposited in all genetically related depositional environments during a complete base-level cycle. Semi-cycle boundaries of a genetic sequence occur at transitions from base-level rise to fall or from base-level fall to rise. In different paleogeographic settings, these transitions are manifested as stratigraphic discontinuities or conformable strata recording increases or decreases in accommodation space, respectively, usually forming sequence boundaries.

在层序地层学中,通常层序划分为1~6级,其中1~3级层序对应构造成因的沉积旋回,属于低频层序(旋回),分别对应于巨层序、超层序和层序;4~6级层序分别对应气候成因的沉积旋回,属于高频层序(旋回),也称米兰科维奇(Milank-ovitch)旋回,分别对应于准层序组、准层序和韵律层。层序地层学研究时,层序划分是基础,层序界面识别是层序划分的关键。一般层序界面有不整合面、海侵上超面、水淹不整合面、古岩溶作用面、火山事件作用面、岩性转换面。不同级别的层序对应着不同的级别的层序界面,如区域的不整合面、构造转换面常常对应着低频层序,而岩性转换面、沉积不整合面等对应着高频层序。In sequence stratigraphy, sequences are usually divided into 1 to 6 levels, among which 1 to 3 levels correspond to tectonic sedimentary cycles, belong to low-frequency sequences (cycles), and correspond to giant sequences, super sequences, and sequences respectively; 4 to 6 levels of sequences correspond to climatic sedimentary cycles, belong to high-frequency sequences (cycles), also known as Milankovitch cycles, and correspond to parasequence groups, parasequences, and rhythmic layers respectively. In sequence stratigraphy research, sequence division is the basis, and sequence interface identification is the key to sequence division. Generally, sequence interfaces include unconformity surfaces, transgression overlay surfaces, flooding unconformity surfaces, paleokarst action surfaces, volcanic event action surfaces, and lithology conversion surfaces. Different levels of sequences correspond to different levels of sequence interfaces. For example, regional unconformity surfaces and tectonic conversion surfaces often correspond to low-frequency sequences, while lithology conversion surfaces and sedimentary unconformity surfaces correspond to high-frequency sequences.

地质上常用的层序界面确定方法主要有:岩性岩相变化、岩心观察、INPEFA曲线、小波变化频谱。然而以碳酸盐岩为主要研究对象的地区,岩相包括颗粒岩灰岩、含颗粒泥粉晶灰岩、泥晶灰岩(含颗粒)、云岩及云质灰岩、含膏泥晶灰岩等,发育多套薄层浅滩,生屑滩项较为发育,受多旋回影响,发育多期多套滩体。对于非均质性较强的碳酸盐岩地层,现有的层序界面确定方法通常只能反映低频层序地层的边界,不能识别更高频层序地层格架要求,目前技术方案无法有效确定高频地震层序地层的层序边界。The commonly used methods for determining sequence boundaries in geology are: lithology and lithofacies changes, core observation, INPEFA curve, and wavelet variation spectrum. However, in areas where carbonate rocks are the main research object, the lithofacies include grainstone limestone, grain-containing mud-powder limestone, mud-crystal limestone (containing particles), dolomite and dolomitic limestone, gypsum-containing mud-crystal limestone, etc., and multiple sets of thin-layered shallows are developed. The bioclastic beach is relatively developed. Affected by multiple cycles, multiple stages and multiple sets of beach bodies are developed. For carbonate rock formations with strong heterogeneity, the existing sequence boundary determination methods can usually only reflect the boundaries of low-frequency sequence formations, and cannot identify the requirements of higher-frequency sequence formation frameworks. The current technical solutions cannot effectively determine the sequence boundaries of high-frequency seismic sequence formations.

发明内容Summary of the invention

第一方面,本发明实施例提供一种高频地震层序地层的层序边界确定方法,可建立更精准的高频层序边界体,使得识别的高频地震层序地层的层序边界精度更高,该方法包括:In a first aspect, an embodiment of the present invention provides a method for determining a sequence boundary of a high-frequency seismic sequence stratum, which can establish a more accurate high-frequency sequence boundary volume, so that the sequence boundary of the identified high-frequency seismic sequence stratum is more accurate. The method comprises:

根据目标区域的目的层段的三维地震数据体,计算地质模型网格;Calculate the geological model grid based on the three-dimensional seismic data volume of the target layer segment in the target area;

根据地质模型网格,生成相对地质年代模型;Generate a relative geological age model based on the geological model grid;

对相对地质年代模型进行处理分析,提取初始的基于地震的中低频第一层序边界数据体;The relative geological age model is processed and analyzed to extract the initial seismic-based low- and medium-frequency first sequence boundary data volume;

从初始的基于地震的中低频第一层序边界数据体中,提取目标井点处目的层段的基于地震的中低频第一次层序边界曲线;Extracting the seismic-based medium-low-frequency first sequence boundary curve of the target layer segment at the target well point from the initial seismic-based medium-low-frequency first sequence boundary data volume;

对基于地震的中低频第一次层序边界曲线进行去基线处理,获得基于地震的去基线处理后的中低频第二次层序边界曲线;Performing baseline removal processing on the first sequence boundary curve of medium and low frequency based on seismic data to obtain the second sequence boundary curve of medium and low frequency based on seismic data after baseline removal processing;

根据基于地震的去基线处理后的中低频第二次层序边界曲线,通过第一次波形差异反演,获得基于地震的第二层序边界数据体;According to the low- and medium-frequency second sequence boundary curve after baseline removal based on seismic, the second sequence boundary data volume based on seismic is obtained through the first waveform difference inversion;

从基于地震的第二层序边界数据体中,提取目标井点处目的层段的基于地震的第三次层序边界曲线;Extracting the seismic-based third sequence boundary curve of the target layer segment at the target well point from the seismic-based second sequence boundary data volume;

以基于地震的第三次层序边界曲线为基础曲线,与目标井点处的反映高频层序边界的伽马曲线、反映高频层序边界的孔隙度曲线、反映高频层序边界的碳酸盐岩颗粒曲线、反映高频层序边界的碳酸盐岩纹理曲线、反映层序边界的碳酸盐岩缝合线频率曲线、反映层序边界的碳酸盐岩的沥青含量曲线和反映层序边界的碳酸盐岩的白云岩含量曲线进行融合,获得基于地震的高频第十次层序边界曲线;The third sequence boundary curve based on seismic is used as the basic curve, and is fused with the gamma curve reflecting the high-frequency sequence boundary at the target well point, the porosity curve reflecting the high-frequency sequence boundary, the carbonate rock grain curve reflecting the high-frequency sequence boundary, the carbonate rock texture curve reflecting the high-frequency sequence boundary, the carbonate rock suture line frequency curve reflecting the sequence boundary, the asphalt content curve of the carbonate rock reflecting the sequence boundary and the dolomite content curve of the carbonate rock reflecting the sequence boundary to obtain the high-frequency tenth sequence boundary curve based on seismic;

根据基于地震的高频第十次层序边界曲线,对目标区域的目的层段再进行第二次波形差异反演,获得基于地震的高频第三层序边界数据体;According to the high-frequency tenth-order sequence boundary curve based on seismic data, a second waveform difference inversion is performed on the target layer section in the target area to obtain the high-frequency third-order sequence boundary data volume based on seismic data.

根据基于地震的高频第三层序边界数据体,识别出高频地震层序地层的层序边界。The sequence boundaries of high-frequency seismic sequence stratigraphy are identified based on the high-frequency third sequence boundary data volume based on seismic.

第二方面,本发明实施例还提供一种高频地震层序地层的层序边界确定装置,可建立更精准的高频层序边界体,使得识别的高频地震层序地层的层序边界精度更高,该装置包括:In a second aspect, an embodiment of the present invention further provides a device for determining a sequence boundary of a high-frequency seismic sequence stratum, which can establish a more accurate high-frequency sequence boundary volume, so that the sequence boundary of the identified high-frequency seismic sequence stratum is more accurate, and the device comprises:

地质模型网格计算模块,用于根据目标区域的目的层段的三维地震数据体,计算地质模型网格;A geological model grid calculation module is used to calculate the geological model grid according to the three-dimensional seismic data volume of the target layer section in the target area;

相对地质年代模型生成模块,用于根据地质模型网格,生成相对地质年代模型;A relative geological age model generation module is used to generate a relative geological age model based on a geological model grid;

层序厚度边界数据体提取模块,用于对相对地质年代模型进行处理分析,提取初始的基于地震的中低频第一层序边界数据体;The sequence thickness boundary data volume extraction module is used to process and analyze the relative geological age model and extract the initial seismic-based medium- and low-frequency first sequence boundary data volume;

基于地震的层序边界曲线,用于从初始的基于地震的中低频第一层序边界数据体中,提取目标井点处目的层段的基于地震的中低频第一次层序边界曲线;对基于地震的中低频第一次层序边界曲线进行去基线处理,获得基于地震的去基线处理后的中低频第二次层序边界曲线;根据基于地震的去基线处理后的中低频第二次层序边界曲线,通过第一次波形差异反演,获得基于地震的第二层序边界数据体;从基于地震的第二层序边界数据体中,提取目标井点处目的层段的基于地震的第三次层序边界曲线;Seismic-based sequence boundary curves are used to extract seismic-based medium-low frequency first sequence boundary curves of target layer segments at target well points from initial seismic-based medium-low frequency first sequence boundary data volumes; perform baseline removal on seismic-based medium-low frequency first sequence boundary curves to obtain seismic-based medium-low frequency second sequence boundary curves after baseline removal; obtain seismic-based second sequence boundary data volumes through first waveform difference inversion based on seismic-based medium-low frequency second sequence boundary curves after baseline removal; extract seismic-based third sequence boundary curves of target layer segments at target well points from seismic-based second sequence boundary data volumes;

融合处理模块,用于以基于地震的第三次层序边界曲线为基础曲线,与目标井点处的反映高频层序边界的伽马曲线、反映高频层序边界的孔隙度曲线、反映高频层序边界的碳酸盐岩颗粒曲线、反映高频层序边界的碳酸盐岩纹理曲线、反映层序边界的碳酸盐岩缝合线频率曲线、反映层序边界的碳酸盐岩的沥青含量曲线和反映层序边界的碳酸盐岩的白云岩含量曲线进行融合,获得基于地震的高频第十次层序边界曲线;A fusion processing module is used to fuse the third-order sequence boundary curve based on seismic as a basic curve with the gamma curve reflecting the high-frequency sequence boundary at the target well point, the porosity curve reflecting the high-frequency sequence boundary, the carbonate rock particle curve reflecting the high-frequency sequence boundary, the carbonate rock texture curve reflecting the high-frequency sequence boundary, the carbonate rock suture line frequency curve reflecting the sequence boundary, the asphalt content curve of the carbonate rock reflecting the sequence boundary and the dolomite content curve of the carbonate rock reflecting the sequence boundary, so as to obtain the high-frequency tenth-order sequence boundary curve based on seismic;

高频地震层序边界识别模块,用于根据基于地震的高频第十次层序边界曲线,对目标区域的目的层段再进行第二次波形差异反演,获得基于地震的高频第三层序边界数据体;根据基于地震的高频第三层序边界数据体,识别出高频地震层序地层的层序边界。The high-frequency seismic sequence boundary identification module is used to perform a second waveform difference inversion on the target layer segment in the target area based on the high-frequency tenth sequence boundary curve based on seismic, and obtain the high-frequency third sequence boundary data body based on seismic; based on the high-frequency third sequence boundary data body based on seismic, the sequence boundary of the high-frequency seismic sequence strata is identified.

第三方面,本发明实施例还提供一种计算机设备,包括存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序,所述处理器执行所述计算机程序时实现上述高频地震层序地层的层序边界确定方法。In a third aspect, an embodiment of the present invention further provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned method for determining the stratigraphic boundaries of high-frequency seismic sequence strata when executing the computer program.

第四方面,本发明实施例还提供一种计算机可读存储介质,所述计算机可读存储介质存储有计算机程序,所述计算机程序被处理器执行时实现上述高频地震层序地层的层序边界确定方法。In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned method for determining the sequence boundaries of high-frequency seismic sequence strata is implemented.

第五方面,本发明实施例还提供一种计算机程序产品,所述计算机程序产品包括计算机程序,所述计算机程序被处理器执行时实现上述高频地震层序地层的层序边界确定方法。In a fifth aspect, an embodiment of the present invention further provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, it implements the above-mentioned method for determining the sequence boundaries of high-frequency seismic sequence strata.

本发明实施例中,根据目标区域的目的层段的三维地震数据体,计算地质模型网格;根据地质模型网格,生成相对地质年代模型;对相对地质年代模型进行处理分析,提取初始的基于地震的中低频第一层序边界数据体;从初始的基于地震的中低频第一层序边界数据体中,提取目标井点处目的层段的基于地震的中低频第一次层序边界曲线;对基于地震的中低频第一次层序边界曲线进行去基线处理,获得基于地震的去基线处理后的中低频第二次层序边界曲线;根据基于地震的去基线处理后的中低频第二次层序边界曲线,通过第一次波形差异反演,获得基于地震的第二层序边界数据体;从基于地震的第二层序边界数据体中,提取目标井点处目的层段的基于地震的第三次层序边界曲线;以基于地震的第三次层序边界曲线为基础曲线,与目标井点处的反映高频层序边界的伽马曲线、反映高频层序边界的孔隙度曲线、反映高频层序边界的碳酸盐岩颗粒曲线、反映高频层序边界的碳酸盐岩纹理曲线、反映层序边界的碳酸盐岩缝合线频率曲线、反映层序边界的碳酸盐岩的沥青含量曲线和反映层序边界的碳酸盐岩的白云岩含量曲线进行融合,获得基于地震的高频第十次层序边界曲线;根据基于地震的高频第十次层序边界曲线,对目标区域的目的层段再进行第二次波形差异反演,获得基于地震的高频第三层序边界数据体;根据基于地震的高频第三层序边界数据体,识别出高频地震层序地层的层序边界。与现有的层序界面确定方法相比,本发明实施例在提取目标井点处目的层段的基于地震的中低频第一次层序边界曲线后,经过多次处理,包括基线处理、反演处理、提取处理和与多种反映高频层序边界的曲线、反映层序边界的曲线进行融合,获得准确度的高频层序边界曲线,最后进行基于波形差异的反演,获得高频层序边界数据体,根据高频层序边界数据体,识别出高频地震层序地层的层序边界,在高频层序边界体内,数值越大,越接近为层序边界,且上述过程融合了目标井点处的伽马曲线、孔隙度曲线,所反演的层序边界特征更明显,进而提高用地震-地质-测井融合信息识别层序界面体的准确性和精度,使得识别的高频地震层序地层的层序边界精度更高。In an embodiment of the present invention, a geological model grid is calculated based on a three-dimensional seismic data volume of a target layer segment in a target area; a relative geological age model is generated based on the geological model grid; the relative geological age model is processed and analyzed to extract an initial seismic-based medium-low frequency first sequence boundary data volume; a seismic-based medium-low frequency first sequence boundary curve of the target layer segment at a target well point is extracted from the initial seismic-based medium-low frequency first sequence boundary data volume; a seismic-based medium-low frequency first sequence boundary curve is subjected to baseline removal processing to obtain a seismic-based medium-low frequency second sequence boundary curve after baseline removal; a seismic-based second sequence boundary data volume is obtained through first waveform difference inversion based on the seismic-based medium-low frequency second sequence boundary curve after baseline removal; and a seismic-based second sequence boundary data volume is extracted from the seismic-based second sequence boundary data volume. a third sequence boundary curve based on seismic; taking the third sequence boundary curve based on seismic as the basic curve, the gamma curve reflecting the high-frequency sequence boundary at the target well point, the porosity curve reflecting the high-frequency sequence boundary, the carbonate rock particle curve reflecting the high-frequency sequence boundary, the carbonate rock texture curve reflecting the high-frequency sequence boundary, the carbonate rock suture line frequency curve reflecting the sequence boundary, the asphalt content curve of the carbonate rock reflecting the sequence boundary and the dolomite content curve of the carbonate rock reflecting the sequence boundary are integrated to obtain the tenth high-frequency sequence boundary curve based on seismic; according to the tenth high-frequency sequence boundary curve based on seismic, the target layer section in the target area is subjected to a second waveform difference inversion to obtain the third high-frequency sequence boundary data body based on seismic; according to the third high-frequency sequence boundary data body based on seismic, the sequence boundary of the high-frequency seismic sequence strata is identified. Compared with the existing sequence interface determination method, after extracting the seismic-based medium- and low-frequency first sequence boundary curve of the target layer segment at the target well point, the embodiment of the present invention undergoes multiple processing, including baseline processing, inversion processing, extraction processing and fusion with multiple curves reflecting high-frequency sequence boundaries and curves reflecting sequence boundaries, to obtain an accurate high-frequency sequence boundary curve, and finally performs inversion based on waveform differences to obtain a high-frequency sequence boundary data body. According to the high-frequency sequence boundary data body, the sequence boundary of the high-frequency seismic sequence strata is identified. In the high-frequency sequence boundary body, the larger the value, the closer it is to the sequence boundary. The above process fuses the gamma curve and porosity curve at the target well point, and the inverted sequence boundary features are more obvious, thereby improving the accuracy and precision of identifying the sequence interface body using seismic-geological-well logging fusion information, so that the sequence boundary of the identified high-frequency seismic sequence strata is more accurate.

附图说明BRIEF DESCRIPTION OF THE DRAWINGS

为了更清楚地说明本发明实施例或现有技术中的技术方案,下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍,显而易见地,下面描述中的附图仅仅是本发明的一些实施例,对于本领域普通技术人员来讲,在不付出创造性劳动的前提下,还可以根据这些附图获得其他的附图。在附图中:In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. In the drawings:

图1为本发明实施例中高频地震层序地层的层序边界确定方法的流程图;FIG1 is a flow chart of a method for determining sequence boundaries of high-frequency seismic sequence strata in an embodiment of the present invention;

图2为本发明实施例中计算地质模型网格的流程图;FIG2 is a flow chart of calculating a geological model grid in an embodiment of the present invention;

图3为本发明实施例中生成相对地质年代模型的流程图;FIG3 is a flow chart of generating a relative geological age model in an embodiment of the present invention;

图4为本发明实施例中多曲线融合的流程图;FIG4 is a flow chart of multi-curve fusion in an embodiment of the present invention;

图5为本发明实施例中根据该地区的三维地震数据体计算的相对地质年代模型的示例图;FIG5 is an example diagram of a relative geological age model calculated based on a three-dimensional seismic data volume in the region according to an embodiment of the present invention;

图6为本发明实施例中对相对地质年代模型进行分析提取初始的基于地震的中低频第一层序边界数据体的连井剖面示例图;6 is an example diagram of a well-connected profile obtained by analyzing the relative geological age model and extracting the initial seismic-based medium- and low-frequency first sequence boundary data volume in an embodiment of the present invention;

图7为本发明实施例中基于地震的层序边界曲线的示例图;FIG7 is an example diagram of a sequence boundary curve based on earthquakes in an embodiment of the present invention;

图8为本发明实施例中通过第一次波形差异反演获得基于地震的第二层序边界数据体的连井剖面示例图;FIG8 is an example diagram of a well-connected cross section of a second sequence boundary data volume based on seismic data obtained by the first waveform difference inversion in an embodiment of the present invention;

图9为本发明实施例中伽马曲线处理前后对比图;FIG9 is a comparison diagram of gamma curves before and after processing according to an embodiment of the present invention;

图10为本发明实施例中孔隙度曲线处理前后对比图;FIG10 is a comparison diagram of porosity curves before and after processing in an embodiment of the present invention;

图11为本发明实施例中融合获得高频层序边界曲线的过程示例;FIG11 is an example of a process of fusing and obtaining a high-frequency sequence boundary curve in an embodiment of the present invention;

图12为本发明实施例中高频层序边界数据体的连井剖面示例;FIG12 is an example of a well-connected section of a high-frequency sequence boundary data volume in an embodiment of the present invention;

图13为本发明实施例的高频地震层序地层的层序边界确定装置的结构框图;FIG13 is a structural block diagram of a device for determining sequence boundaries of high-frequency seismic sequence strata according to an embodiment of the present invention;

图14为本发明实施例中计算机设备的示意图。FIG. 14 is a schematic diagram of a computer device in an embodiment of the present invention.

具体实施方式Detailed ways

为使本发明实施例的目的、技术方案和优点更加清楚明白,下面结合附图对本发明实施例做进一步详细说明。在此,本发明的示意性实施例及其说明用于解释本发明,但并不作为对本发明的限定。To make the purpose, technical solution and advantages of the embodiments of the present invention more clear, the embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings. Here, the exemplary embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

图1为本发明实施例中高频地震层序地层的层序边界确定方法的流程图,包括:FIG1 is a flow chart of a method for determining sequence boundaries of high-frequency seismic sequence strata according to an embodiment of the present invention, comprising:

步骤101,根据目标区域的目的层段的三维地震数据体,计算地质模型网格;Step 101, calculating a geological model grid according to a three-dimensional seismic data volume of a target layer segment in a target area;

步骤102,根据地质模型网格,生成相对地质年代模型;Step 102, generating a relative geological age model according to the geological model grid;

步骤103,对相对地质年代模型进行处理分析,提取初始的基于地震的中低频第一层序边界数据体;Step 103, processing and analyzing the relative geological age model to extract the initial seismic-based medium-low frequency first sequence boundary data volume;

步骤104,从初始的基于地震的中低频第一层序边界数据体中,提取目标井点处目的层段的基于地震的中低频第一次层序边界曲线;Step 104, extracting the seismic-based medium-low-frequency first sequence boundary curve of the target layer segment at the target well point from the initial seismic-based medium-low-frequency first sequence boundary data volume;

步骤105,对基于地震的中低频第一次层序边界曲线进行去基线处理,获得基于地震的去基线处理后的中低频第二次层序边界曲线;Step 105, performing baseline removal processing on the medium-low frequency first sequence boundary curve based on seismic data to obtain the medium-low frequency second sequence boundary curve after baseline removal based on seismic data;

步骤106,根据基于地震的去基线处理后的中低频第二次层序边界曲线,通过第一次波形差异反演,获得基于地震的第二层序边界数据体;Step 106, obtaining a second sequence boundary data volume based on seismic data by performing a first waveform difference inversion based on the low- and medium-frequency second sequence boundary curve after the seismic baseline removal process;

步骤107,从基于地震的第二层序边界数据体中,提取目标井点处目的层段的基于地震的第三次层序边界曲线;Step 107, extracting a third-order sequence boundary curve based on seismic data of a target layer segment at a target well point from the second-order sequence boundary data volume based on seismic data;

步骤108,以基于地震的第三次层序边界曲线为基础曲线,与目标井点处的反映高频层序边界的伽马曲线、反映高频层序边界的孔隙度曲线、反映高频层序边界的碳酸盐岩颗粒曲线、反映高频层序边界的碳酸盐岩纹理曲线、反映层序边界的碳酸盐岩缝合线频率曲线、反映层序边界的碳酸盐岩的沥青含量曲线和反映层序边界的碳酸盐岩的白云岩含量曲线进行融合,获得基于地震的高频第十次层序边界曲线;Step 108, taking the third sequence boundary curve based on seismic as the base curve, the gamma curve reflecting the high-frequency sequence boundary at the target well point, the porosity curve reflecting the high-frequency sequence boundary, the carbonate rock particle curve reflecting the high-frequency sequence boundary, the carbonate rock texture curve reflecting the high-frequency sequence boundary, the carbonate rock suture line frequency curve reflecting the sequence boundary, the asphalt content curve of the carbonate rock reflecting the sequence boundary and the dolomite content curve of the carbonate rock reflecting the sequence boundary are merged to obtain the tenth high-frequency sequence boundary curve based on seismic;

步骤109,根据基于地震的高频第十次层序边界曲线,对目标区域的目的层段再进行第二次波形差异反演,获得基于地震的高频第三层序边界数据体;Step 109, performing a second waveform difference inversion on the target layer section in the target area according to the high-frequency tenth-order sequence boundary curve based on seismic, and obtaining a high-frequency third-order sequence boundary data volume based on seismic;

步骤110,根据基于地震的高频第三层序边界数据体,识别出高频地震层序地层的层序边界。Step 110, identifying the sequence boundaries of the high-frequency seismic sequence strata based on the high-frequency third sequence boundary data volume based on the seismic.

在本发明实施例中,根据目标区域的目的层段的三维地震数据体,计算地质模型网格;根据地质模型网格,生成相对地质年代模型;对相对地质年代模型进行处理分析,提取初始的基于地震的中低频第一层序边界数据体;从初始的基于地震的中低频第一层序边界数据体中,提取目标井点处目的层段的基于地震的中低频第一次层序边界曲线;对基于地震的中低频第一次层序边界曲线进行去基线处理,获得基于地震的去基线处理后的中低频第二次层序边界曲线;根据基于地震的去基线处理后的中低频第二次层序边界曲线,通过第一次波形差异反演,获得基于地震的第二层序边界数据体;从基于地震的第二层序边界数据体中,提取目标井点处目的层段的基于地震的第三次层序边界曲线;以基于地震的第三次层序边界曲线为基础曲线,与目标井点处的反映高频层序边界的伽马曲线、反映高频层序边界的孔隙度曲线、反映高频层序边界的碳酸盐岩颗粒曲线、反映高频层序边界的碳酸盐岩纹理曲线、反映层序边界的碳酸盐岩缝合线频率曲线、反映层序边界的碳酸盐岩的沥青含量曲线和反映层序边界的碳酸盐岩的白云岩含量曲线进行融合,获得基于地震的高频第十次层序边界曲线;根据基于地震的高频第十次层序边界曲线,对目标区域的目的层段再进行第二次波形差异反演,获得基于地震的高频第三层序边界数据体;根据基于地震的高频第三层序边界数据体,识别出高频地震层序地层的层序边界。与现有的层序界面确定方法相比,本发明实施例在提取目标井点处目的层段的基于地震的中低频第一次层序边界曲线后,经过多次处理,包括基线处理、反演处理、提取处理和与多种反映高频层序边界的曲线、反映层序边界的曲线进行融合,获得准确度的高频层序边界曲线,最后进行基于波形差异的反演,获得高频层序边界数据体,根据高频层序边界数据体,识别出高频地震层序地层的层序边界,在高频层序边界体内,数值越大,越接近为层序边界,且上述过程融合了目标井点处的伽马曲线、孔隙度曲线,所反演的层序边界特征更明显,进而提高用地震-地质-测井融合信息识别层序界面体的准确性和精度,使得识别的高频地震层序地层的层序边界精度更高。In an embodiment of the present invention, a geological model grid is calculated based on a three-dimensional seismic data volume of a target layer segment in a target area; a relative geological age model is generated based on the geological model grid; the relative geological age model is processed and analyzed to extract an initial seismic-based medium-low frequency first sequence boundary data volume; from the initial seismic-based medium-low frequency first sequence boundary data volume, a seismic-based medium-low frequency first sequence boundary curve of the target layer segment at a target well point is extracted; the seismic-based medium-low frequency first sequence boundary curve is subjected to baseline removal processing to obtain a seismic-based medium-low frequency second sequence boundary curve after baseline removal; based on the seismic-based medium-low frequency second sequence boundary curve after baseline removal, a seismic-based second sequence boundary data volume is obtained through first waveform difference inversion; from the seismic-based second sequence boundary data volume, the target layer segment at the target well point is extracted a third sequence boundary curve based on seismic; taking the third sequence boundary curve based on seismic as the basic curve, the gamma curve reflecting the high-frequency sequence boundary at the target well point, the porosity curve reflecting the high-frequency sequence boundary, the carbonate rock particle curve reflecting the high-frequency sequence boundary, the carbonate rock texture curve reflecting the high-frequency sequence boundary, the carbonate rock suture line frequency curve reflecting the sequence boundary, the asphalt content curve of the carbonate rock reflecting the sequence boundary and the dolomite content curve of the carbonate rock reflecting the sequence boundary are integrated to obtain the tenth high-frequency sequence boundary curve based on seismic; according to the tenth high-frequency sequence boundary curve based on seismic, the target layer section in the target area is subjected to a second waveform difference inversion to obtain the third high-frequency sequence boundary data body based on seismic; according to the third high-frequency sequence boundary data body based on seismic, the sequence boundary of the high-frequency seismic sequence strata is identified. Compared with the existing sequence interface determination method, after extracting the seismic-based medium- and low-frequency first sequence boundary curve of the target layer segment at the target well point, the embodiment of the present invention undergoes multiple processing, including baseline processing, inversion processing, extraction processing and fusion with multiple curves reflecting high-frequency sequence boundaries and curves reflecting sequence boundaries, to obtain an accurate high-frequency sequence boundary curve, and finally performs inversion based on waveform differences to obtain a high-frequency sequence boundary data body. According to the high-frequency sequence boundary data body, the sequence boundary of the high-frequency seismic sequence strata is identified. In the high-frequency sequence boundary body, the larger the value, the closer it is to the sequence boundary. The above process fuses the gamma curve and porosity curve at the target well point, and the inverted sequence boundary features are more obvious, thereby improving the accuracy and precision of identifying the sequence interface body using seismic-geological-well logging fusion information, so that the sequence boundary of the identified high-frequency seismic sequence strata is more accurate.

在步骤101中,根据目标区域的目的层段的三维地震数据体,计算地质模型网格;In step 101, a geological model grid is calculated based on a three-dimensional seismic data volume of a target layer segment in a target area;

本步骤结合实际测井及地震资料中的三维地震数据体进行计算。This step combines the actual well logging and three-dimensional seismic data in the seismic data for calculation.

参见图2,根据目标区域的目的层段的三维地震数据体,计算地质模型网格,包括:Referring to FIG. 2 , the geological model grid is calculated based on the 3D seismic data volume of the target layer in the target area, including:

步骤201,根据目标区域的目的层段的三维地震数据体,确定初始的地质模型网格;这里提供两种确定初始的地址模型网格的方法。Step 201, determine an initial geological model grid based on the three-dimensional seismic data volume of the target layer segment in the target area; two methods for determining the initial geological model grid are provided here.

在一实施例中,根据目标区域的目的层段的三维地震数据体,确定初始的地质模型网格,包括:In one embodiment, determining an initial geological model grid based on a three-dimensional seismic data volume of a target layer segment in a target area includes:

在所述三维地震数据体存在地震层位数据时,自动追踪三维地震数据体中的地震层位数据,以追踪到的地震层位数据为约束,建立地质模型网格;其中,地震层位数据为在三维地震数据体中已经存在的;When there is seismic layer data in the three-dimensional seismic data volume, the seismic layer data in the three-dimensional seismic data volume is automatically tracked, and a geological model grid is established with the tracked seismic layer data as a constraint; wherein the seismic layer data is already present in the three-dimensional seismic data volume;

在所述三维地震数据体不存在地震层位数据时,对目标区域的目的层段的三维地震数据体中的至少一个种子点,根据波形相似性和相对距离,计算初始的地质模型网格。具体计算时,可采用一定的算法,例如基于边界控制—局部映射的算法等,这里不做限制。When there is no seismic layer data in the three-dimensional seismic data body, an initial geological model grid is calculated for at least one seed point in the three-dimensional seismic data body of the target layer segment of the target area according to waveform similarity and relative distance. When calculating specifically, a certain algorithm may be used, such as an algorithm based on boundary control-local mapping, etc., which is not limited here.

步骤202,将初始的地质模型网格作为当前地质模型网格,重复执行以下步骤,直至当前地质模型网格与三维地震数据体的吻合情况满足预设条件:Step 202: Using the initial geological model grid as the current geological model grid, the following steps are repeatedly performed until the current geological model grid and the three-dimensional seismic data volume are consistent with the preset conditions:

步骤2021,在当前地质模型网格中,交互地修正地震层位间的关联关系;这里每次修正都会对模型网格中节点之间的链接产生影响;Step 2021, in the current geological model grid, interactively correct the association relationship between seismic layers; each correction here will affect the links between nodes in the model grid;

步骤2022,分析修正后的地质模型网格与三维地震数据体的吻合情况;具体实施时可通过预览来分析;Step 2022, analyzing the consistency between the modified geological model grid and the three-dimensional seismic data volume; in specific implementation, the analysis can be performed through preview;

步骤2023,在吻合情况不满足预设条件时,优化当前地质模型网格的参数,并将优化的地质模型网格作为当前地质模型网格。Step 2023, when the matching condition does not meet the preset conditions, optimize the parameters of the current geological model grid, and use the optimized geological model grid as the current geological model grid.

通过上述循环迭代,可获得最优的地质模型网格。Through the above iterative cycles, the optimal geological model grid can be obtained.

在步骤102,根据地质模型网格,生成相对地质年代模型;In step 102, a relative geological age model is generated based on the geological model grid;

参见图3,在一实施例中,根据地质模型网格,生成相对地质年代模型,包括:Referring to FIG3 , in one embodiment, generating a relative geological age model based on a geological model grid includes:

步骤301,对地质模型网格的面元片之间进行连接和插值,获得处理后的地质模型网格;Step 301, connecting and interpolating the facets of the geological model grid to obtain a processed geological model grid;

步骤302,对处理后的地质模型网格中每个像素分配相对地质年代,生成初始相对地质年代模型;Step 302, assigning a relative geological age to each pixel in the processed geological model grid to generate an initial relative geological age model;

步骤303,从初始相对地质年代模型中提取多个层位堆叠体,形成用多个层位堆叠体表示的相对地质年代模型。其中,层位堆叠体一般包括数万个,用数万个层位堆叠体表示的相对地质年代模型的精确更高。Step 303, extract multiple stratigraphic stacks from the initial relative geological age model to form a relative geological age model represented by multiple stratigraphic stacks. The stratigraphic stacks generally include tens of thousands of stratigraphic stacks, and the relative geological age model represented by tens of thousands of stratigraphic stacks is more accurate.

步骤103,对相对地质年代模型进行处理分析,提取初始的基于地震的中低频第一层序边界数据体;层序厚度边界数据体是一种可以反映地层层序边界的属性体数据,可以反映纵向和横向层序边界的变化,并结合地震做层序解释,该数值越大,说明相同地质年代差越大,越可能为层序边界,这是基于地震-地质的全局思维理念建立高频层序地层框架的解释方法。Step 103, the relative geological age model is processed and analyzed to extract the initial low- to medium-frequency first sequence boundary data body based on earthquakes; the sequence thickness boundary data body is an attribute body data that can reflect the stratigraphic sequence boundary, which can reflect the changes in the vertical and horizontal sequence boundaries and be combined with earthquakes for sequence interpretation. The larger the value, the greater the difference in the same geological age, and the more likely it is a sequence boundary. This is an interpretation method for establishing a high-frequency sequence stratigraphic framework based on the global thinking concept of earthquake-geology.

步骤104,从初始的基于地震的中低频第一层序边界数据体中,提取目标井点处目的层段的基于地震的中低频第一次层序边界曲线;Step 104, extracting the seismic-based medium-low-frequency first sequence boundary curve of the target layer segment at the target well point from the initial seismic-based medium-low-frequency first sequence boundary data volume;

在一实施例中,从初始的基于地震的中低频第一层序边界数据体中,提取目标井点处目的层段的基于地震的中低频第一次层序边界曲线,包括:In one embodiment, extracting a seismic-based medium-low-frequency first sequence boundary curve of a target layer segment at a target well point from an initial seismic-based medium-low-frequency first sequence boundary data volume includes:

对基于地震的去基线处理后的中低频第二次层序边界曲线做井震标定和第一次波形差异反演,获得基于地震的第二层序边界数据体。The well-seismic calibration and the first waveform difference inversion are performed on the medium-low frequency second sequence boundary curve after the seismic baseline removal to obtain the seismic second sequence boundary data volume.

对基于地震的中低频第一次层序边界曲线进行去基线处理,获得基于地震的去基线处理后的中低频第二次层序边界曲线,此时得到的地震的去基线处理后的中低频第二次层序边界曲线可以突出从地震数据体获取的层序厚度边界曲线对层序边界的识别能力。The medium-low frequency first sequence boundary curve based on seismic is subjected to baseline removal processing to obtain the medium-low frequency second sequence boundary curve based on seismic after baseline removal processing. The medium-low frequency second sequence boundary curve obtained after baseline removal processing can highlight the recognition ability of the sequence thickness boundary curve obtained from the seismic data body for the sequence boundary.

在步骤108中,以基于地震的第三次层序边界曲线为基础曲线,与目标井点处的反映高频层序边界的伽马曲线、反映高频层序边界的孔隙度曲线、反映高频层序边界的碳酸盐岩颗粒曲线、反映高频层序边界的碳酸盐岩纹理曲线、反映层序边界的碳酸盐岩缝合线频率曲线、反映层序边界的碳酸盐岩的沥青含量曲线和反映层序边界的碳酸盐岩的白云岩含量曲线进行融合,获得基于地震的高频第十次层序边界曲线;In step 108, the third-order sequence boundary curve based on seismic is used as a base curve, and is fused with a gamma curve reflecting high-frequency sequence boundaries at a target well point, a porosity curve reflecting high-frequency sequence boundaries, a carbonate rock grain curve reflecting high-frequency sequence boundaries, a carbonate rock texture curve reflecting high-frequency sequence boundaries, a carbonate rock suture frequency curve reflecting sequence boundaries, an asphalt content curve of carbonate rocks reflecting sequence boundaries, and a dolomite content curve of carbonate rocks reflecting sequence boundaries to obtain a high-frequency tenth-order sequence boundary curve based on seismic;

参见图4,具体融合步骤包括:Referring to FIG. 4 , the specific fusion steps include:

步骤401,以基于地震的第三次层序边界曲线为基础曲线,离散化呈多个列数据点,将反映高频层序边界的伽马曲线进行归一化处理后离散化呈多个列数据点后,叠加到对应深度点的基于地震的第三次层序边界曲线对应的多个列数据点上,融合成基于地震的第四次高频层序边界曲线;Step 401, using the third-order sequence boundary curve based on seismic as a basic curve, discretizing it into a plurality of column data points, normalizing the gamma curve reflecting the high-frequency sequence boundary, discretizing it into a plurality of column data points, superimposing it on the plurality of column data points corresponding to the third-order sequence boundary curve based on seismic at the corresponding depth point, and fusing it into a fourth-order high-frequency sequence boundary curve based on seismic;

在一实施例中,所述方法还包括:In one embodiment, the method further comprises:

对目标井点处的伽马曲线做反向处理,获得反向伽马曲线;Perform reverse processing on the gamma curve at the target well point to obtain a reverse gamma curve;

对反向伽马曲线进行去趋势化处理,获得去趋势化处理后的伽马曲线;Detrending the reverse gamma curve to obtain a detrended gamma curve;

对去趋势化处理后的伽马曲线再进行去除基线处理,获得反映高频层序边界的伽马曲线。The detrended gamma curve is then subjected to baseline removal to obtain a gamma curve reflecting the high-frequency sequence boundary.

步骤402,以基于地震的第四次层序边界曲线为基础曲线,离散化呈多个列数据点,将反映高频层序边界的孔隙度曲线进行归一化处理后离散化呈多个列数据点后,叠加到对应深度点的基于地震的第四次层序边界曲线对应的多个列数据点上,融合成基于地震的第五次高频层序边界曲线;Step 402, using the fourth-order sequence boundary curve based on seismic as a base curve, discretizing it into a plurality of columns of data points, normalizing the porosity curve reflecting the high-frequency sequence boundary, discretizing it into a plurality of columns of data points, and superimposing it on the plurality of columns of data points corresponding to the fourth-order sequence boundary curve based on seismic at the corresponding depth point, and merging them into a fifth-order high-frequency sequence boundary curve based on seismic;

在一实施例中,所述方法还包括:In one embodiment, the method further comprises:

对目标井点处的孔隙度曲线进行去基线化处理,获得反映高频层序边界的孔隙度曲线。The porosity curve at the target well point is de-baselined to obtain a porosity curve reflecting the high-frequency sequence boundary.

步骤403,以基于地震的第五次层序边界曲线为基础曲线,离散化呈多个列数据点,将反映高频层序边界的碳酸盐岩颗粒曲线进行归一化处理后离散化呈多个列数据点后,叠加到对应深度点的基于地震的第五次层序边界曲线对应的多个列数据点上,融合成基于地震的第六次高频层序边界曲线;其中,反映高频层序边界的碳酸盐岩颗粒曲线为碳酸盐岩颗粒量化为从颗粒灰岩到泥质灰岩的多个列数据点形成的曲线;Step 403, using the fifth sequence boundary curve based on seismic data as a base curve, discretizing it into a plurality of columns of data points, normalizing and discretizing the carbonate rock grain curve reflecting the high-frequency sequence boundary into a plurality of columns of data points, superimposing the curve onto the plurality of columns of data points corresponding to the fifth sequence boundary curve based on seismic data at the corresponding depth point, and merging them into a sixth high-frequency sequence boundary curve based on seismic data; wherein the carbonate rock grain curve reflecting the high-frequency sequence boundary is a curve formed by quantizing carbonate rock grains into a plurality of columns of data points from grain limestone to argillaceous limestone;

例如,量化为从颗粒灰岩到泥质灰岩的多个列数据点可以为-7、-6、-5、-4、-3、-2、-1、0、1、2、3、4、5、6,负值越大表示颗粒越小,泥质含量越增加,正值越大表示碳酸盐岩颗粒越大,碳酸盐岩颗粒含量越增加。For example, multiple column data points quantified from granular limestone to muddy limestone can be -7, -6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6. The larger the negative value, the smaller the particles and the higher the mud content. The larger the positive value, the larger the carbonate rock particles and the higher the carbonate rock particle content.

其中,碳酸盐岩颗粒越大表示海水活动能量越强,因此,融合了归一化的碳酸盐岩颗粒曲线可以较好地反应碳酸盐岩层序边界信息。Among them, the larger the carbonate rock particles, the stronger the energy of seawater activity. Therefore, the carbonate rock particle curve integrated with normalization can better reflect the boundary information of carbonate rock sequence.

步骤404,以基于地震的第六次层序边界曲线为基础曲线,离散化呈多个列数据点,将反映高频层序边界的碳酸盐岩纹理曲线进行归一化处理后离散化呈多个列数据点后,叠加到对应深度点的基于地震的第六次层序边界曲线对应的多个列数据点上,融合成基于地震的第七次高频层序边界曲线;其中,反映高频层序边界的碳酸盐岩纹理曲线为碳酸盐岩的岩石纹理结构量化为多个列数据点形成的曲线;Step 404, using the sixth sequence boundary curve based on seismic as a base curve, discretizing it into a plurality of column data points, normalizing and discretizing the carbonate rock texture curve reflecting the high-frequency sequence boundary into a plurality of column data points, superimposing it onto the plurality of column data points corresponding to the sixth sequence boundary curve based on seismic at the corresponding depth point, and merging them into the seventh high-frequency sequence boundary curve based on seismic; wherein the carbonate rock texture curve reflecting the high-frequency sequence boundary is a curve formed by quantizing the rock texture structure of carbonate rock into a plurality of column data points;

例如碳酸盐岩的岩石纹理结构量化1到15的整数,数值越大表示纹理越粗;For example, the rock texture structure of carbonate rocks is quantified as integers from 1 to 15, with larger values indicating coarser texture;

其中,碳酸盐岩岩石纹理曲线表示碳酸盐岩沉积层序的结构和沉积旋回的特征,融合碳酸盐岩纹理曲线,更为精细反映碳酸盐岩的高频层序边界。Among them, the carbonate rock texture curve represents the structure of the carbonate sedimentary sequence and the characteristics of the sedimentary cycle. The fusion of the carbonate rock texture curve can more finely reflect the high-frequency sequence boundaries of the carbonate rock.

步骤405,以基于地震的第七次层序边界曲线为基础曲线,离散化呈多个列数据点,将反映高频层序边界的碳酸盐岩的缝合线频率曲线进行归一化处理后离散化呈多个列数据点后,叠加到对应深度点的基于地震的第七次层序边界曲线对应的多个列数据点上,融合成基于地震的第八次高频层序边界曲线;其中,反映高频层序边界的碳酸盐岩的缝合线频率曲线为碳酸盐岩的缝合线频率量化为多个列数据点形成的曲线;Step 405, taking the seventh-order sequence boundary curve based on seismic as the base curve, discretizing it into a plurality of column data points, normalizing and discretizing the suture frequency curve of carbonate rocks reflecting the high-frequency sequence boundary into a plurality of column data points, and superimposing it onto the plurality of column data points corresponding to the seventh-order sequence boundary curve based on seismic at the corresponding depth point, and merging them into the eighth-order high-frequency sequence boundary curve based on seismic; wherein the suture frequency curve of carbonate rocks reflecting the high-frequency sequence boundary is a curve formed by quantizing the suture frequency of carbonate rocks into a plurality of column data points;

例如,碳酸盐岩的缝合线频率量化为1至9的整数,数值越大,表示缝合线越多。For example, the stylolite frequency of carbonate rocks is quantified as an integer from 1 to 9, where a larger number indicates more stylolites.

其中,反映高频层序边界的碳酸盐岩的缝合线频率曲线反映成岩作用所引起的构造和层序边界的变化,缝合线数量越大,反映海退后引起的进积特征越强,粗粒沉积引起的层序边界越明显。Among them, the suture frequency curve of carbonate rocks reflecting high-frequency sequence boundaries reflects the changes in structure and sequence boundaries caused by diagenesis. The larger the number of sutures, the stronger the progradation characteristics caused by sea retreat, and the more obvious the sequence boundaries caused by coarse-grained deposition.

步骤406,以基于地震的第八次层序边界曲线为基础曲线,离散化呈多个列数据点,将反映层序边界的碳酸盐岩的沥青含量曲线进行归一化处理后离散化呈多个列数据点后,叠加到对应深度点的基于地震的第八次层序边界曲线对应的多个列数据点上,融合成基于地震的第九次高频层序边界曲线;其中,反映层序边界的碳酸盐岩的沥青含量曲线为碳酸盐岩的沥青含量量化为多个列数据点形成的曲线;Step 406, using the eighth order sequence boundary curve based on seismic as a base curve, discretizing it into a plurality of column data points, normalizing the asphalt content curve of carbonate rock reflecting the sequence boundary, discretizing it into a plurality of column data points, and superimposing it on the plurality of column data points corresponding to the eighth order sequence boundary curve based on seismic at the corresponding depth point, and merging them into the ninth order high-frequency sequence boundary curve based on seismic; wherein the asphalt content curve of carbonate rock reflecting the sequence boundary is a curve formed by quantifying the asphalt content of carbonate rock into a plurality of column data points;

例如,碳酸盐岩的沥青含量量化为0.1至0.9,数值越大,表示沥青含量越多;For example, the bitumen content of carbonate rocks is quantified from 0.1 to 0.9, with the larger value indicating more bitumen content;

其中,碳酸盐岩的沥青含量曲线反映碳酸盐岩成藏过程温度、压力、组分的变化,所引起层序边界的变化。因此,融合反映层序边界的碳酸盐岩的沥青含量曲线可以帮助精细识别层序边界。Among them, the asphalt content curve of carbonate rocks reflects the changes in temperature, pressure, and composition during the carbonate rock accumulation process, which causes changes in sequence boundaries. Therefore, integrating the asphalt content curve of carbonate rocks that reflects sequence boundaries can help finely identify sequence boundaries.

步骤407,以基于地震的第九次层序边界曲线为基础曲线,离散化呈多个列数据点,将反映层序边界的碳酸盐岩的白云岩含量曲线进行归一化处理后离散化呈多个列数据点后,叠加到对应深度点的基于地震的第九次层序边界曲线对应的多个列数据点上,融合成基于地震的第十次高频层序边界曲线;其中,反映层序边界的碳酸盐岩的白云岩含量曲线为碳酸盐岩的白云岩到灰岩含量量化为多个列数据点形成的曲线。Step 407, taking the ninth order sequence boundary curve based on seismic as a base curve, discretizing it into a plurality of columns of data points, normalizing the dolomite content curve of carbonate rock reflecting the sequence boundary, discretizing it into a plurality of columns of data points, and superimposing it on the plurality of columns of data points corresponding to the ninth order sequence boundary curve based on seismic at the corresponding depth point, and merging them into the tenth order high-frequency sequence boundary curve based on seismic; wherein the dolomite content curve of carbonate rock reflecting the sequence boundary is a curve formed by quantifying the dolomite to limestone content of carbonate rock into a plurality of columns of data points.

例如,碳酸盐岩的白云岩到灰岩含量量化为0.1至0.9,数值越大,表示白云岩含量越多;其中,白云岩含量越高表示碳酸盐岩沉积环境处于暴露环境,海水就越浅,碳酸盐岩层序位于上半旋回的海退环境,融合反映层序边界的碳酸盐岩的白云岩含量曲线更精细化反映高频层序边界。For example, the dolomite to limestone content of carbonate rocks is quantified as 0.1 to 0.9, and the larger the value, the more dolomite content. Among them, the higher the dolomite content indicates that the carbonate rock depositional environment is in an exposed environment, the shallower the sea water, and the carbonate rock sequence is located in the regressive environment of the upper half cycle. The dolomite content curve of the carbonate rock that reflects the sequence boundary more finely reflects the high-frequency sequence boundary.

最后得到的基于地震的第十次高频层序边界曲线可以反映高频层序边界的信息。The tenth high-frequency sequence boundary curve finally obtained based on seismic data can reflect the information of high-frequency sequence boundaries.

在步骤109,根据基于地震的高频第十次层序边界曲线,对目标区域的目的层段再进行第二次波形差异反演,获得基于地震的高频第三层序边界数据体,此时的高频层序边界数据体更清晰且精度更高;In step 109, according to the high-frequency tenth-order sequence boundary curve based on seismic data, a second waveform difference inversion is performed on the target layer section in the target area to obtain a high-frequency third-order sequence boundary data body based on seismic data. At this time, the high-frequency sequence boundary data body is clearer and more accurate.

在步骤110,根据基于地震的高频第三层序边界数据体,识别出高频地震层序地层的层序边界,最后用基于高频层序界面数据体全局思维理念,可自动识别获得精度更高的高频地震层序地层的层序边界。In step 110, the sequence boundaries of the high-frequency seismic sequence stratigraphy are identified based on the high-frequency third sequence boundary data body based on seismic. Finally, the sequence boundaries of the high-frequency seismic sequence stratigraphy with higher accuracy can be automatically identified using the global thinking concept based on the high-frequency sequence interface data body.

本发明实施例提出的方法可用于碳酸盐岩层序界面,解决了现有获得碳酸盐岩层序界面过程中只能获得低旋回界面,层序界面分辨率低的技术问题。在以碳酸盐岩油气藏开发为主的地区,碳酸盐岩储层非均质性的成因机理是制约高效开发的基础地质问题,特别是对于复杂碳酸盐岩幕式层序旋回、沉积模式及相应的多期成岩演化的研究薄弱,需要通过建立高频沉积旋回层序地层格架,辅助开展碳酸盐岩成岩演化史以及多元地质因素耦合控储机制研究。因此,本发明方法具有广阔应用前景。The method proposed in the embodiment of the present invention can be used for carbonate sequence interfaces, which solves the technical problem that only low-cycle interfaces can be obtained in the existing process of obtaining carbonate sequence interfaces, and the sequence interface resolution is low. In areas where carbonate oil and gas reservoirs are mainly developed, the genetic mechanism of carbonate reservoir heterogeneity is a basic geological problem that restricts efficient development, especially for complex carbonate curtain sequence cycles, sedimentary patterns and corresponding multi-stage diagenetic evolution. Research is weak, and it is necessary to establish a high-frequency sedimentary cycle sequence stratigraphic framework to assist in the study of carbonate diagenetic evolution history and the coupled reservoir control mechanism of multiple geological factors. Therefore, the method of the present invention has broad application prospects.

下面给出一个具体的实施例来说明本发明提出的方法的具体应用。A specific embodiment is given below to illustrate the specific application of the method proposed in the present invention.

以碳酸盐岩油气藏开发为主的某一个地区为例,图5为本发明实施例中根据该地区的三维地震数据体计算的相对地质年代模型的示例图,其中,图5中的(a)为三维地震数据体,图5中的(b)为地质模型网格,图5中的(c)为相对地质年代模型。图6为本发明实施例中对相对地质年代模型进行分析提取初始的基于地震的中低频第一层序边界数据体的连井剖面示例图,显示每个地震样点的相对地质年代的瞬时变化,突出显示地质层的收敛和发散区域。对于不整合面、地层终止(下伏、上超)、剥蚀、压实和地层厚度敏感。初始的基于地震的中低频第一层序边界数据体等于相对等时的地质时间除以地震双程反射时间间隔。如果分母地震双程反射时间间隔相同,则分子相对等时地质时间越大,层序厚度边界数据体就越大,表示地层越厚。Taking a certain area where carbonate oil and gas reservoirs are mainly developed as an example, FIG. 5 is an example diagram of a relative geological age model calculated based on a three-dimensional seismic data body in the embodiment of the present invention, wherein (a) in FIG. 5 is a three-dimensional seismic data body, (b) in FIG. 5 is a geological model grid, and (c) in FIG. 5 is a relative geological age model. FIG. 6 is an example diagram of a well-connected profile of an initial seismic-based medium- and low-frequency first sequence boundary data body analyzed and extracted in an embodiment of the present invention for the relative geological age model, showing the instantaneous change of the relative geological age of each seismic sample point, highlighting the convergence and divergence areas of the geological layer. It is sensitive to unconformity surfaces, formation termination (underlying, onlapping), erosion, compaction, and formation thickness. The initial seismic-based medium- and low-frequency first sequence boundary data body is equal to the relative isochronous geological time divided by the seismic two-way reflection time interval. If the denominator seismic two-way reflection time interval is the same, the larger the numerator relative isochronous geological time, the larger the sequence thickness boundary data body, indicating that the formation is thicker.

图7为本发明实施例中基于地震的层序边界曲线的示例图,其中,图7中的(a)为基于地震的中低频第一次层序边界曲线,图7中的(b)为对初始层序边界曲线做去基线处理处理后的曲线。图8为本发明实施例中通过第一次波形差异反演获得基于地震的第二层序边界数据体的连井剖面示例图,最后提取的基于地震的第三次层序边界曲线可以突出从地震数据获取的层序厚度边界曲线对层序边界的识别能力。FIG7 is an example diagram of a sequence boundary curve based on seismic in an embodiment of the present invention, wherein (a) in FIG7 is a first sequence boundary curve of medium and low frequency based on seismic, and (b) in FIG7 is a curve after baseline removal processing of the initial sequence boundary curve. FIG8 is an example diagram of a well-connected profile of a second sequence boundary data volume based on seismic obtained by first waveform difference inversion in an embodiment of the present invention, and the third sequence boundary curve based on seismic extracted finally can highlight the recognition ability of the sequence thickness boundary curve obtained from seismic data for sequence boundaries.

图9为本发明实施例中伽马曲线处理前后对比图,其中,图9中的(a)为初始的伽马曲线,图9中的(b)为反映高频层序边界的伽马曲线。FIG9 is a comparison diagram of gamma curves before and after processing in an embodiment of the present invention, wherein FIG9(a) is an initial gamma curve, and FIG9(b) is a gamma curve reflecting the high-frequency sequence boundary.

图10为本发明实施例中孔隙度曲线处理前后对比图,其中,图10中的(a)为初始的孔隙度曲线线,图10中的(b)为反映高频层序边界的孔隙度曲线。FIG10 is a comparison diagram of the porosity curves before and after processing in an embodiment of the present invention, wherein FIG10 (a) is the initial porosity curve, and FIG10 (b) is the porosity curve reflecting the high-frequency sequence boundary.

图11为本发明实施例中融合获得基于地震的高频第十次层序边界曲线的过程示例,其中,图11中的(a)为基于地震的第三次层序边界曲线,图11中的(b)为处理后的层序边界曲线,图11中的(c)为初始的伽马曲线,图11中的(d)为反映高频层序边界的伽马曲线,图11中的(e)为初始的孔隙度曲线线,图11中的(f)为反映高频层序边界的孔隙度曲线,图11中的(g)为融合获得的基于地震的第五次高频层序边界曲线,后续可再继续融合其他曲线,最后获得基于地震的第十次高频层序边界曲线。图12为本发明实施例中基于地震的高频第三层序边界数据体的连井剖面示例,此时的基于地震的高频第三层序边界数据体更清晰且精度更高,最后用基于高频层序界面数据体全局思维理念,可自动识别获得精度更高的高频地震层序地层的层序边界。FIG11 is an example of the process of obtaining the high-frequency tenth sequence boundary curve based on seismic by fusion in an embodiment of the present invention, wherein (a) in FIG11 is the third sequence boundary curve based on seismic, (b) in FIG11 is the sequence boundary curve after processing, (c) in FIG11 is the initial gamma curve, (d) in FIG11 is the gamma curve reflecting the high-frequency sequence boundary, (e) in FIG11 is the initial porosity curve, (f) in FIG11 is the porosity curve reflecting the high-frequency sequence boundary, and (g) in FIG11 is the fifth high-frequency sequence boundary curve based on seismic obtained by fusion. Other curves can be further fused later to finally obtain the tenth high-frequency sequence boundary curve based on seismic. FIG12 is an example of a well-connected section of the high-frequency third sequence boundary data body based on seismic in an embodiment of the present invention. At this time, the high-frequency third sequence boundary data body based on seismic is clearer and more accurate. Finally, the sequence boundary of the high-frequency seismic sequence strata with higher accuracy can be automatically identified by using the global thinking concept based on the high-frequency sequence interface data body.

本发明实施例还提出一种高频地震层序地层的层序边界确定生成装置,其原理与高频地震层序地层的层序边界确定生成方法类似,这里不再赘述。The embodiment of the present invention further provides a device for determining and generating sequence boundaries of high-frequency seismic sequence strata, the principle of which is similar to the method for determining and generating sequence boundaries of high-frequency seismic sequence strata, and will not be described in detail here.

图13为本发明实施例中高频地震层序地层的层序边界确定生成装置的示意图,包括:FIG13 is a schematic diagram of a device for determining and generating sequence boundaries of high-frequency seismic sequence strata according to an embodiment of the present invention, comprising:

地质模型网格计算模块1301,用于根据目标区域的目的层段的三维地震数据体,计算地质模型网格;The geological model grid calculation module 1301 is used to calculate the geological model grid according to the three-dimensional seismic data volume of the target layer segment in the target area;

相对地质年代模型生成模块1302,用于根据地质模型网格,生成相对地质年代模型;A relative geological age model generation module 1302 is used to generate a relative geological age model according to the geological model grid;

层序厚度边界数据体提取模块1303,用于对相对地质年代模型进行处理分析,提取初始的基于地震的中低频第一层序边界数据体;The sequence thickness boundary data volume extraction module 1303 is used to process and analyze the relative geological age model and extract the initial low-frequency first sequence boundary data volume based on earthquakes;

基于地震的层序边界曲线1304,用于从初始的基于地震的中低频第一层序边界数据体中,提取目标井点处目的层段的基于地震的中低频第一次层序边界曲线;对基于地震的中低频第一次层序边界曲线进行去基线处理,获得基于地震的去基线处理后的中低频第二次层序边界曲线;根据基于地震的去基线处理后的中低频第二次层序边界曲线,通过第一次波形差异反演,获得基于地震的第二层序边界数据体;从基于地震的第二层序边界数据体中,提取目标井点处目的层段的基于地震的第三次层序边界曲线;Seismic-based sequence boundary curve 1304 is used to extract a seismic-based medium-low frequency first sequence boundary curve of a target layer segment at a target well point from an initial seismic-based medium-low frequency first sequence boundary data volume; perform baseline removal processing on the seismic-based medium-low frequency first sequence boundary curve to obtain a seismic-based medium-low frequency second sequence boundary curve after baseline removal; obtain a seismic-based second sequence boundary data volume through a first waveform difference inversion based on the seismic-based medium-low frequency second sequence boundary curve after baseline removal; extract a seismic-based third sequence boundary curve of a target layer segment at a target well point from the seismic-based second sequence boundary data volume;

融合处理模块1305,用于以基于地震的第三次层序边界曲线为基础曲线,与目标井点处的反映高频层序边界的伽马曲线、反映高频层序边界的孔隙度曲线、反映高频层序边界的碳酸盐岩颗粒曲线、反映高频层序边界的碳酸盐岩纹理曲线、反映层序边界的碳酸盐岩缝合线频率曲线、反映层序边界的碳酸盐岩的沥青含量曲线和反映层序边界的碳酸盐岩的白云岩含量曲线进行融合,获得基于地震的高频第十次层序边界曲线;A fusion processing module 1305 is used to fuse the third-order sequence boundary curve based on seismic as a basic curve with a gamma curve reflecting the high-frequency sequence boundary at a target well point, a porosity curve reflecting the high-frequency sequence boundary, a carbonate rock particle curve reflecting the high-frequency sequence boundary, a carbonate rock texture curve reflecting the high-frequency sequence boundary, a carbonate rock suture frequency curve reflecting the sequence boundary, an asphalt content curve of carbonate rocks reflecting the sequence boundary, and a dolomite content curve of carbonate rocks reflecting the sequence boundary, so as to obtain a high-frequency tenth-order sequence boundary curve based on seismic;

高频地震层序边界识别模块1306,用于根据基于地震的高频第十次层序边界曲线,对目标区域的目的层段再进行第二次波形差异反演,获得基于地震的高频第三层序边界数据体;根据基于地震的高频第三层序边界数据体,识别出高频地震层序地层的层序边界。The high-frequency seismic sequence boundary identification module 1306 is used to perform a second waveform difference inversion on the target layer segment in the target area based on the high-frequency tenth-order sequence boundary curve based on seismic, and obtain the high-frequency third-order sequence boundary data body based on seismic; and identify the sequence boundaries of the high-frequency seismic sequence strata based on the high-frequency third-order sequence boundary data body based on seismic.

在一实施例中,地质模型网格计算模块具体用于:In one embodiment, the geological model grid calculation module is specifically used for:

根据目标区域的目的层段的三维地震数据体,确定初始的地质模型网格;Determine the initial geological model grid based on the 3D seismic data volume of the target layer segment in the target area;

将初始的地质模型网格作为当前地质模型网格,重复执行以下步骤,直至当前地质模型网格与三维地震数据体的吻合情况满足预设条件:The initial geological model grid is used as the current geological model grid, and the following steps are repeated until the current geological model grid and the 3D seismic data volume meet the preset conditions:

在当前地质模型网格中,交互地修正地震层位间的关联关系;Interactively modify the correlation between seismic layers in the current geological model grid;

分析修正后的地质模型网格与三维地震数据体的吻合情况;Analyze the consistency between the modified geological model grid and the 3D seismic data volume;

在吻合情况不满足预设条件时,优化当前地质模型网格的参数,并将优化的地质模型网格作为当前地质模型网格。When the matching situation does not meet the preset conditions, the parameters of the current geological model grid are optimized, and the optimized geological model grid is used as the current geological model grid.

在一实施例中,地质模型网格计算模块具体用于:In one embodiment, the geological model grid calculation module is specifically used for:

在所述三维地震数据体存在地震层位数据时,自动追踪三维地震数据体中的地震层位数据,以追踪到的地震层位数据为约束,建立地质模型网格;When the three-dimensional seismic data volume contains seismic layer data, the seismic layer data in the three-dimensional seismic data volume is automatically tracked, and a geological model grid is established with the tracked seismic layer data as a constraint;

在所述三维地震数据体不存在地震层位数据时,对目标区域的目的层段的三维地震数据体中的至少一个种子点,根据波形相似性和相对距离,计算初始的地质模型网格。When there is no seismic layer data in the three-dimensional seismic data volume, an initial geological model grid is calculated for at least one seed point in the three-dimensional seismic data volume of the target layer segment in the target area according to waveform similarity and relative distance.

在一实施例中,相对地质年代模型生成模块具体用于:In one embodiment, the relative geological age model generation module is specifically used to:

对地质模型网格的面元片之间进行连接和插值,获得处理后的地质模型网格;Connecting and interpolating the surface elements of the geological model grid to obtain a processed geological model grid;

对处理后的地质模型网格中每个像素分配相对地质年代,生成初始相对地质年代模型;Assigning relative geological age to each pixel in the processed geological model grid to generate an initial relative geological age model;

从初始相对地质年代模型中提取多个层位堆叠体,形成用多个层位堆叠体表示的相对地质年代模型。A plurality of stratigraphic stacks are extracted from the initial relative geological age model to form a relative geological age model represented by the plurality of stratigraphic stacks.

在一实施例中,基于地震的层序边界曲线具体用于:In one embodiment, the seismic-based sequence boundary curve is specifically used to:

对基于地震的去基线处理后的中低频第二次层序边界曲线做井震标定和第一次波形差异反演,获得基于地震的第二层序边界数据体。The well-seismic calibration and the first waveform difference inversion are performed on the medium-low frequency second sequence boundary curve after the seismic baseline removal to obtain the seismic second sequence boundary data volume.

在一实施例中,融合处理模块具体用于:In one embodiment, the fusion processing module is specifically used for:

对目标井点处的伽马曲线做反向处理,获得反向伽马曲线;Perform reverse processing on the gamma curve at the target well point to obtain a reverse gamma curve;

对反向伽马曲线进行去趋势化处理,获得去趋势化处理后的伽马曲线;Detrending the reverse gamma curve to obtain a detrended gamma curve;

对去趋势化处理后的伽马曲线再进行去除基线处理,获得反映高频层序边界的伽马曲线。The detrended gamma curve is then subjected to baseline removal to obtain a gamma curve reflecting the high-frequency sequence boundary.

在一实施例中,融合处理模块具体用于:In one embodiment, the fusion processing module is specifically used for:

对目标井点处的孔隙度曲线进行去基线化处理,获得反映高频层序边界的孔隙度曲线。The porosity curve at the target well point is de-baselined to obtain a porosity curve reflecting the high-frequency sequence boundary.

在一实施例中,融合处理模块具体用于:In one embodiment, the fusion processing module is specifically used for:

以基于地震的第三次层序边界曲线为基础曲线,离散化呈多个列数据点,将反映高频层序边界的伽马曲线进行归一化处理后离散化呈多个列数据点后,叠加到对应深度点的基于地震的第三次层序边界曲线对应的多个列数据点上,融合成基于地震的第四次高频层序边界曲线;The third sequence boundary curve based on earthquake is used as the basic curve, which is discretized into multiple columns of data points. The gamma curve reflecting the high-frequency sequence boundary is normalized and discretized into multiple columns of data points, which are then superimposed on the multiple columns of data points corresponding to the third sequence boundary curve based on earthquake at the corresponding depth point, and merged into the fourth high-frequency sequence boundary curve based on earthquake;

以基于地震的第四次层序边界曲线为基础曲线,离散化呈多个列数据点,将反映高频层序边界的孔隙度曲线进行归一化处理后离散化呈多个列数据点后,叠加到对应深度点的基于地震的第四次层序边界曲线对应的多个列数据点上,融合成基于地震的第五次高频层序边界曲线;The fourth-order sequence boundary curve based on seismic is used as the basic curve, which is discretized into multiple columns of data points. The porosity curve reflecting the high-frequency sequence boundary is normalized and discretized into multiple columns of data points, which are then superimposed on the multiple columns of data points corresponding to the fourth-order sequence boundary curve based on seismic at the corresponding depth point, and merged into the fifth-order high-frequency sequence boundary curve based on seismic.

以基于地震的第五次层序边界曲线为基础曲线,离散化呈多个列数据点,将反映高频层序边界的碳酸盐岩颗粒曲线进行归一化处理后离散化呈多个列数据点后,叠加到对应深度点的基于地震的第五次层序边界曲线对应的多个列数据点上,融合成基于地震的第六次高频层序边界曲线;其中,反映高频层序边界的碳酸盐岩颗粒曲线为碳酸盐岩颗粒量化为从颗粒灰岩到泥质灰岩的多个列数据点形成的曲线;The fifth sequence boundary curve based on seismic data is used as a basic curve and discretized into multiple columns of data points. The carbonate rock grain curve reflecting the high-frequency sequence boundary is normalized and discretized into multiple columns of data points, which are then superimposed on the multiple columns of data points corresponding to the fifth sequence boundary curve based on seismic data at the corresponding depth point to merge into the sixth high-frequency sequence boundary curve based on seismic data; wherein the carbonate rock grain curve reflecting the high-frequency sequence boundary is a curve formed by quantizing carbonate rock grains into multiple columns of data points from grain limestone to argillaceous limestone;

以基于地震的第六次层序边界曲线为基础曲线,离散化呈多个列数据点,将反映高频层序边界的碳酸盐岩纹理曲线进行归一化处理后离散化呈多个列数据点后,叠加到对应深度点的基于地震的第六次层序边界曲线对应的多个列数据点上,融合成基于地震的第七次高频层序边界曲线;其中,反映高频层序边界的碳酸盐岩纹理曲线为碳酸盐岩的岩石纹理结构量化为多个列数据点形成的曲线;The sixth sequence boundary curve based on seismic data is used as a basic curve and discretized into multiple columns of data points. The carbonate rock texture curve reflecting the high-frequency sequence boundary is normalized and discretized into multiple columns of data points, which are then superimposed on the multiple columns of data points corresponding to the sixth sequence boundary curve based on seismic data at the corresponding depth point to merge into the seventh high-frequency sequence boundary curve based on seismic data; wherein the carbonate rock texture curve reflecting the high-frequency sequence boundary is a curve formed by quantizing the rock texture structure of carbonate rock into multiple columns of data points;

以基于地震的第七次层序边界曲线为基础曲线,离散化呈多个列数据点,将反映高频层序边界的碳酸盐岩的缝合线频率曲线进行归一化处理后离散化呈多个列数据点后,叠加到对应深度点的基于地震的第七次层序边界曲线对应的多个列数据点上,融合成基于地震的第八次高频层序边界曲线;其中,反映高频层序边界的碳酸盐岩的缝合线频率曲线为碳酸盐岩的缝合线频率量化为多个列数据点形成的曲线;The seventh-order sequence boundary curve based on seismic is used as the basic curve, which is discretized into a plurality of columns of data points. The suture frequency curve of carbonate rocks reflecting the high-frequency sequence boundary is normalized and discretized into a plurality of columns of data points, which are then superimposed on the plurality of columns of data points corresponding to the seventh-order sequence boundary curve based on seismic at the corresponding depth point, and merged into the eighth-order high-frequency sequence boundary curve based on seismic; wherein the suture frequency curve of carbonate rocks reflecting the high-frequency sequence boundary is a curve formed by quantizing the suture frequency of carbonate rocks into a plurality of columns of data points;

以基于地震的第八次层序边界曲线为基础曲线,离散化呈多个列数据点,将反映层序边界的碳酸盐岩的沥青含量曲线进行归一化处理后离散化呈多个列数据点后,叠加到对应深度点的基于地震的第八次层序边界曲线对应的多个列数据点上,融合成基于地震的第九次高频层序边界曲线;其中,反映层序边界的碳酸盐岩的沥青含量曲线为碳酸盐岩的沥青含量量化为多个列数据点形成的曲线;The eighth sequence boundary curve based on seismic is used as the basic curve, which is discretized into multiple columns of data points. The asphalt content curve of carbonate rock reflecting the sequence boundary is normalized and discretized into multiple columns of data points, which are then superimposed on the multiple columns of data points corresponding to the eighth sequence boundary curve based on seismic at the corresponding depth point, and merged into the ninth high-frequency sequence boundary curve based on seismic; wherein the asphalt content curve of carbonate rock reflecting the sequence boundary is a curve formed by quantifying the asphalt content of carbonate rock into multiple columns of data points;

以基于地震的第九次层序边界曲线为基础曲线,离散化呈多个列数据点,将反映层序边界的碳酸盐岩的白云岩含量曲线进行归一化处理后离散化呈多个列数据点后,叠加到对应深度点的基于地震的第九次层序边界曲线对应的多个列数据点上,融合成基于地震的第十次高频层序边界曲线;其中,反映层序边界的碳酸盐岩的白云岩含量曲线为碳酸盐岩的白云岩到灰岩含量量化为多个列数据点形成的曲线。The ninth sequence boundary curve based on seismic is taken as the basic curve and discretized into multiple columns of data points. The dolomite content curve of carbonate rock reflecting the sequence boundary is normalized and discretized into multiple columns of data points, which are then superimposed on the multiple columns of data points corresponding to the ninth sequence boundary curve based on seismic at the corresponding depth point to merge into the tenth high-frequency sequence boundary curve based on seismic; wherein, the dolomite content curve of carbonate rock reflecting the sequence boundary is a curve formed by quantifying the dolomite to limestone content of carbonate rock into multiple columns of data points.

综上所述,在本发明实施例提出的方法及装置中,根据目标区域的目的层段的三维地震数据体,计算地质模型网格;根据地质模型网格,生成相对地质年代模型;对相对地质年代模型进行处理分析,提取初始的基于地震的中低频第一层序边界数据体;从初始的基于地震的中低频第一层序边界数据体中,提取目标井点处目的层段的基于地震的中低频第一次层序边界曲线;对基于地震的中低频第一次层序边界曲线进行去基线处理,获得基于地震的去基线处理后的中低频第二次层序边界曲线;根据基于地震的去基线处理后的中低频第二次层序边界曲线,通过第一次波形差异反演,获得基于地震的第二层序边界数据体;从基于地震的第二层序边界数据体中,提取目标井点处目的层段的基于地震的第三次层序边界曲线;以基于地震的第三次层序边界曲线为基础曲线,与目标井点处的反映高频层序边界的伽马曲线、反映高频层序边界的孔隙度曲线、反映高频层序边界的碳酸盐岩颗粒曲线、反映高频层序边界的碳酸盐岩纹理曲线、反映层序边界的碳酸盐岩缝合线频率曲线、反映层序边界的碳酸盐岩的沥青含量曲线和反映层序边界的碳酸盐岩的白云岩含量曲线进行融合,获得基于地震的高频第十次层序边界曲线;根据基于地震的高频第十次层序边界曲线,对目标区域的目的层段再进行第二次波形差异反演,获得基于地震的高频第三层序边界数据体;根据基于地震的高频第三层序边界数据体,识别出高频地震层序地层的层序边界。与现有的层序界面确定方法相比,本发明实施例在提取目标井点处目的层段的基于地震的中低频第一次层序边界曲线后,经过多次处理,包括基线处理、反演处理、提取处理和与多种反映高频层序边界的曲线、反映层序边界的曲线进行融合,获得准确度的高频层序边界曲线,最后进行基于波形差异的反演,获得高频层序边界数据体,根据高频层序边界数据体,识别出高频地震层序地层的层序边界,在高频层序边界体内,数值越大,越接近为层序边界,且上述过程融合了目标井点处的伽马曲线、孔隙度曲线,所反演的层序边界特征更明显,进而提高用地震-地质-测井融合信息识别层序界面体的准确性和精度,使得识别的高频地震层序地层的层序边界精度更高。In summary, in the method and device proposed in the embodiment of the present invention, a geological model grid is calculated based on the three-dimensional seismic data volume of the target layer segment in the target area; a relative geological age model is generated based on the geological model grid; the relative geological age model is processed and analyzed to extract the initial seismic-based medium-low frequency first sequence boundary data volume; from the initial seismic-based medium-low frequency first sequence boundary data volume, the seismic-based medium-low frequency first sequence boundary curve of the target layer segment at the target well point is extracted; the seismic-based medium-low frequency first sequence boundary curve is subjected to baseline removal processing to obtain the seismic-based medium-low frequency second sequence boundary curve after baseline removal; based on the seismic-based medium-low frequency second sequence boundary curve after baseline removal, the seismic-based second sequence boundary data volume is obtained through the first waveform difference inversion; the target well point is extracted from the seismic-based second sequence boundary data volume. A third seismic-based sequence boundary curve of the target layer segment at the well point; taking the third seismic-based sequence boundary curve as the basic curve, the gamma curve reflecting the high-frequency sequence boundary, the porosity curve reflecting the high-frequency sequence boundary, the carbonate rock particle curve reflecting the high-frequency sequence boundary, the carbonate rock texture curve reflecting the high-frequency sequence boundary, the carbonate rock suture line frequency curve reflecting the sequence boundary, the asphalt content curve of the carbonate rock reflecting the sequence boundary and the dolomite content curve of the carbonate rock reflecting the sequence boundary at the target well point are integrated to obtain a high-frequency tenth seismic-based sequence boundary curve; according to the high-frequency tenth seismic-based sequence boundary curve, a second waveform difference inversion is performed on the target layer segment in the target area to obtain a high-frequency third sequence boundary data body based on seismic; according to the high-frequency third sequence boundary data body based on seismic, the sequence boundary of the high-frequency seismic sequence stratum is identified. Compared with the existing sequence interface determination method, after extracting the seismic-based medium- and low-frequency first sequence boundary curve of the target layer segment at the target well point, the embodiment of the present invention undergoes multiple processing, including baseline processing, inversion processing, extraction processing and fusion with multiple curves reflecting high-frequency sequence boundaries and curves reflecting sequence boundaries, to obtain an accurate high-frequency sequence boundary curve, and finally performs inversion based on waveform differences to obtain a high-frequency sequence boundary data body. According to the high-frequency sequence boundary data body, the sequence boundary of the high-frequency seismic sequence strata is identified. In the high-frequency sequence boundary body, the larger the value, the closer it is to the sequence boundary. The above process fuses the gamma curve and porosity curve at the target well point, and the inverted sequence boundary features are more obvious, thereby improving the accuracy and precision of identifying the sequence interface body using seismic-geological-well logging fusion information, so that the sequence boundary of the identified high-frequency seismic sequence strata is more accurate.

本发明实施例还提供一种计算机设备,图14为本发明实施例中计算机设备的示意图,所述计算机设备1400包括存储器1410、处理器1420及存储在存储器1410上并可在处理器1420上运行的计算机程序1430,所述处理器1420执行所述计算机程序1430时实现上述高频地震层序地层的层序边界确定方法。An embodiment of the present invention further provides a computer device. FIG14 is a schematic diagram of a computer device in an embodiment of the present invention. The computer device 1400 includes a memory 1410, a processor 1420, and a computer program 1430 stored in the memory 1410 and executable on the processor 1420. When the processor 1420 executes the computer program 1430, the above-mentioned method for determining the sequence boundaries of high-frequency seismic sequence strata is implemented.

本发明实施例还提供一种计算机可读存储介质,所述计算机可读存储介质存储有计算机程序,所述计算机程序被处理器执行时实现上述高频地震层序地层的层序边界确定方法。An embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned method for determining the sequence boundary of high-frequency seismic sequence strata is implemented.

本发明实施例还提供一种计算机程序产品,所述计算机程序产品包括计算机程序,所述计算机程序被处理器执行时实现上述高频地震层序地层的层序边界确定方法。An embodiment of the present invention further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the method for determining the sequence boundaries of high-frequency seismic sequence strata is implemented.

本领域内的技术人员应明白,本发明的实施例可提供为方法、系统、或计算机程序产品。因此,本发明可采用完全硬件实施例、完全软件实施例、或结合软件和硬件方面的实施例的形式。而且,本发明可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

本发明是参照根据本发明实施例的方法、设备(系统)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器,使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。The present invention is described with reference to the flowchart and/or block diagram of the method, device (system), and computer program product according to the embodiment of the present invention. It should be understood that each process and/or box in the flowchart and/or block diagram, as well as the combination of the process and/or box in the flowchart and/or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device for implementing the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.

这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的计算机可读存储器中,使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品,该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device that implements the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.

这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上,使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理,从而在计算机或其他可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。These computer program instructions may also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.

以上所述的具体实施例,对本发明的目的、技术方案和有益效果进行了进一步详细说明,所应理解的是,以上所述仅为本发明的具体实施例而已,并不用于限定本发明的保护范围,凡在本发明的精神和原则之内,所做的任何修改、等同替换、改进等,均应包含在本发明的保护范围之内。The specific embodiments described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims (19)

1. A method for determining a sequence boundary of a high frequency seismic sequence formation, comprising:
calculating a geological model grid according to the three-dimensional seismic data volume of the target interval of the target area;
generating a relative geologic time model according to the geologic model grid;
processing and analyzing the relative geologic time model, and extracting an initial medium-low frequency first sequence boundary data body based on earthquake;
Extracting a seismic-based medium-low frequency first sequence boundary curve of a target interval at a target well point from an initial seismic-based medium-low frequency first sequence boundary data volume;
performing baseline removal processing on the middle-low frequency first sequence boundary curve based on the earthquake to obtain a middle-low frequency second sequence boundary curve after the baseline removal processing based on the earthquake;
according to the medium-low frequency second sequence boundary curve after the baseline removal processing based on the earthquake, obtaining a second sequence boundary data body based on the earthquake through first waveform difference inversion;
extracting a third sub-sequence boundary curve based on the earthquake of the target interval at the target well point from the second sequence boundary data body based on the earthquake;
taking a third sequence boundary curve based on an earthquake as a basic curve, and fusing the third sequence boundary curve with a gamma curve reflecting a high-frequency sequence boundary, a porosity curve reflecting the high-frequency sequence boundary, a carbonate grain curve reflecting the high-frequency sequence boundary, a carbonate suture line frequency curve reflecting the sequence boundary, an asphalt content curve reflecting the carbonate of the sequence boundary and a dolomite content curve reflecting the carbonate of the sequence boundary at a target well point to obtain a tenth sequence boundary curve based on the earthquake;
According to a high-frequency tenth-order boundary curve based on the earthquake, carrying out second waveform difference inversion on a target interval of the target area to obtain a Gao Pindi three-order boundary data body based on the earthquake;
based on the Gao Pindi three-layer sequence boundary data body based on the earthquake, the sequence boundary of the high-frequency earthquake sequence stratum is identified.
2. The method of claim 1, wherein computing a geologic model grid from the three-dimensional seismic data volume of the interval of interest of the target area comprises:
determining an initial geological model grid according to the three-dimensional seismic data volume of the target interval of the target area;
taking the initial geological model grid as the current geological model grid, and repeatedly executing the following steps until the matching condition of the current geological model grid and the three-dimensional seismic data volume meets the preset condition:
interactively correcting the association relation among the seismic horizons in the current geological model grid;
analyzing the coincidence condition of the corrected geological model grid and the three-dimensional seismic data volume;
when the fit condition does not meet the preset condition, optimizing parameters of the current geological model grid, and taking the optimized geological model grid as the current geological model grid.
3. The method of claim 2, wherein determining an initial geologic model grid from the three-dimensional seismic data volume of the destination interval of the target area comprises:
when the three-dimensional seismic data volume has seismic horizon data, automatically tracking the seismic horizon data in the three-dimensional seismic data volume, and establishing a geological model grid by taking the tracked seismic horizon data as a constraint;
and when the three-dimensional seismic data volume does not contain the seismic horizon data, calculating an initial geological model grid according to the waveform similarity and the relative distance for at least one seed point in the three-dimensional seismic data volume of the target interval of the target area.
4. The method of claim 1, wherein generating a relative geologic time model from a geologic model grid comprises:
connecting and interpolating the surface element sheets of the geological model grid to obtain a processed geological model grid;
distributing relative geologic time to each pixel in the processed geologic model grid to generate an initial relative geologic time model;
a plurality of horizon stacks are extracted from the initial relative geologic time model to form a relative geologic time model represented by the plurality of horizon stacks.
5. The method of claim 1, wherein obtaining the seismic-based second sequence boundary data volume by first waveform difference inversion from the seismic-based de-baselined medium and low frequency second sequence boundary curve comprises:
and (3) performing well-shock calibration and first-time waveform difference inversion on the middle-low frequency second sequence boundary curve after the base line removal processing based on the earthquake to obtain a second sequence boundary data body based on the earthquake.
6. The method as recited in claim 1, further comprising:
performing reverse processing on the gamma curve at the target well point to obtain a reverse gamma curve;
performing trending treatment on the reverse gamma curve to obtain a trended gamma curve;
and (3) removing the base line of the gamma curve after trending treatment to obtain a gamma curve reflecting the boundary of the high-frequency sequence.
7. The method as recited in claim 1, further comprising:
and performing baseline removal treatment on the porosity curve at the target well point to obtain a porosity curve reflecting the boundary of the high-frequency sequence.
8. The method of claim 1, wherein the blending with the gamma curve reflecting the high frequency sequence boundary, the porosity curve reflecting the high frequency sequence boundary, the carbonate grain curve reflecting the high frequency sequence boundary, the carbonate suture line frequency curve reflecting the sequence boundary, the asphalt content curve reflecting the carbonate of the sequence boundary, and the dolomite content curve reflecting the carbonate of the sequence boundary at the target well point, respectively, to obtain the high frequency tenth sequence boundary curve based on the earthquake comprises:
Discretizing to form a plurality of column data points by taking the third-order boundary curve based on the earthquake as a basic curve, discretizing the gamma curve reflecting the high-frequency sequence boundary to form a plurality of column data points after normalization treatment, superposing the column data points on a plurality of column data points corresponding to the third-order boundary curve based on the earthquake of the corresponding depth point, and fusing the column data points into a fourth high-frequency sequence boundary curve based on the earthquake;
discretizing to form a plurality of column data points by taking a fourth time sequence boundary curve based on the earthquake as a basic curve, discretizing to form a plurality of column data points after carrying out normalization processing on a porosity curve reflecting a high-frequency sequence boundary, superposing the column data points on a plurality of column data points corresponding to the fourth time sequence boundary curve based on the earthquake of a corresponding depth point, and fusing the column data points into a fifth high-frequency sequence boundary curve based on the earthquake;
discretizing a carbonate particle curve reflecting a high-frequency sequence boundary into a plurality of column data points by taking a fifth-order sequence boundary curve based on the earthquake as a basic curve, discretizing the carbonate particle curve reflecting the high-frequency sequence boundary into a plurality of column data points after normalization treatment, and then superposing the column data points on a plurality of column data points corresponding to the fifth-order sequence boundary curve based on the earthquake of a corresponding depth point to fuse the column data points into a sixth high-frequency sequence boundary curve based on the earthquake; wherein the carbonate particle curve reflecting the high frequency sequence boundary is a curve formed by quantifying carbonate particles into a plurality of column data points from granular limestone to argillaceous limestone;
Discretizing a carbonate texture curve reflecting a high-frequency sequence boundary into a plurality of column data points by taking a sixth-order sequence boundary curve based on the earthquake as a basic curve, discretizing the carbonate texture curve reflecting the high-frequency sequence boundary into a plurality of column data points after normalization treatment, and then superposing the column data points on a plurality of column data points corresponding to the sixth-order sequence boundary curve based on the earthquake of the corresponding depth point to fuse the column data points into a seventh high-frequency sequence boundary curve based on the earthquake; wherein, the carbonate rock texture curve reflecting the high-frequency sequence boundary is a curve formed by quantifying the rock texture structure of the carbonate rock into a plurality of column data points;
discretizing a series of data points by taking a seventh layer sequence boundary curve based on the earthquake as a basic curve, discretizing a suture line frequency curve of carbonate rock reflecting a high-frequency layer sequence boundary into a plurality of series of data points after normalization treatment, superposing the series of data points on a plurality of series of data points corresponding to the seventh layer sequence boundary curve based on the earthquake of a corresponding depth point, and fusing the series of data points into an eighth high-frequency layer sequence boundary curve based on the earthquake; wherein, the suture frequency curve of the carbonate rock reflecting the high-frequency sequence boundary is a curve formed by quantifying the suture frequency of the carbonate rock into a plurality of column data points;
Discretizing to form a plurality of column data points by taking an eighth sequence boundary curve based on the earthquake as a basic curve, discretizing to form a plurality of column data points after normalizing a carbonate rock asphalt content curve reflecting the sequence boundary, and then superposing the column data points on a plurality of column data points corresponding to the eighth sequence boundary curve based on the earthquake of the corresponding depth points to fuse the column data points into a ninth high-frequency sequence boundary curve based on the earthquake; wherein, the asphalt content curve of the carbonate rock reflecting the layer sequence boundary is a curve formed by quantifying the asphalt content of the carbonate rock into a plurality of column data points;
discretizing to form a plurality of column data points by taking a ninth-order layer sequence boundary curve based on the earthquake as a basic curve, discretizing to form a plurality of column data points after carrying out normalization treatment on a dolomite content curve of carbonate rock reflecting the layer sequence boundary, superposing the column data points on a plurality of column data points corresponding to the ninth-order layer sequence boundary curve based on the earthquake of a corresponding depth point, and fusing the column data points into a tenth high-frequency layer sequence boundary curve based on the earthquake; wherein, the dolomite content curve of the carbonate rock reflecting the sequence boundary is a curve formed by quantifying the dolomite to limestone content of the carbonate rock into a plurality of column data points.
9. A high frequency seismic sequence boundary determination apparatus for a sequence of layers, comprising:
the geological model grid calculation module is used for calculating geological model grids according to the three-dimensional seismic data volume of the target interval of the target area;
the relative geologic time model generation module is used for generating a relative geologic time model according to the geologic model grid;
the layer sequence thickness boundary data body extraction module is used for processing and analyzing the relative geologic time model and extracting an initial medium-low frequency first layer sequence boundary data body based on earthquake;
the system comprises a seismic-based interval boundary curve, a first-frequency-based interval boundary curve and a second-frequency-based interval boundary curve, wherein the seismic-based interval boundary curve is used for extracting a target interval at a target well point from an initial seismic-based middle-low frequency first interval boundary data volume; performing baseline removal processing on the middle-low frequency first sequence boundary curve based on the earthquake to obtain a middle-low frequency second sequence boundary curve after the baseline removal processing based on the earthquake; according to the medium-low frequency second sequence boundary curve after the baseline removal processing based on the earthquake, obtaining a second sequence boundary data body based on the earthquake through first waveform difference inversion; extracting a third sub-sequence boundary curve based on the earthquake of the target interval at the target well point from the second sequence boundary data body based on the earthquake;
The fusion processing module is used for fusing a third sequence boundary curve based on the earthquake with a gamma curve reflecting a high-frequency sequence boundary, a porosity curve reflecting the high-frequency sequence boundary, a carbonate particle curve reflecting the high-frequency sequence boundary, a carbonate texture curve reflecting the high-frequency sequence boundary, a carbonate suture line frequency curve reflecting the sequence boundary, an asphalt content curve reflecting the carbonate of the sequence boundary and an dolomite content curve reflecting the carbonate of the sequence boundary at a target well point to obtain a tenth sequence boundary curve based on the earthquake;
the high-frequency earthquake sequence boundary identification module is used for carrying out second waveform difference inversion on a target interval of the target area according to a high-frequency tenth sequence boundary curve based on the earthquake to obtain a Gao Pindi sequence boundary data body based on the earthquake; based on the Gao Pindi three-layer sequence boundary data body based on the earthquake, the sequence boundary of the high-frequency earthquake sequence stratum is identified.
10. The apparatus of claim 9, wherein the geologic model grid computing module is configured to:
determining an initial geological model grid according to the three-dimensional seismic data volume of the target interval of the target area;
Taking the initial geological model grid as the current geological model grid, and repeatedly executing the following steps until the matching condition of the current geological model grid and the three-dimensional seismic data volume meets the preset condition:
interactively correcting the association relation among the seismic horizons in the current geological model grid;
analyzing the coincidence condition of the corrected geological model grid and the three-dimensional seismic data volume;
when the fit condition does not meet the preset condition, optimizing parameters of the current geological model grid, and taking the optimized geological model grid as the current geological model grid.
11. The apparatus of claim 10, wherein the geologic model grid computing module is configured to:
when the three-dimensional seismic data volume has seismic horizon data, automatically tracking the seismic horizon data in the three-dimensional seismic data volume, and establishing a geological model grid by taking the tracked seismic horizon data as a constraint;
and when the three-dimensional seismic data volume does not contain the seismic horizon data, calculating an initial geological model grid according to the waveform similarity and the relative distance for at least one seed point in the three-dimensional seismic data volume of the target interval of the target area.
12. The apparatus of claim 9, wherein the relative geologic time model generation module is configured to:
Connecting and interpolating the surface element sheets of the geological model grid to obtain a processed geological model grid;
distributing relative geologic time to each pixel in the processed geologic model grid to generate an initial relative geologic time model;
a plurality of horizon stacks are extracted from the initial relative geologic time model to form a relative geologic time model represented by the plurality of horizon stacks.
13. The apparatus of claim 9, wherein the seismic-based interval boundary curve is specifically configured to:
and (3) performing well-shock calibration and first-time waveform difference inversion on the middle-low frequency second sequence boundary curve after the base line removal processing based on the earthquake to obtain a second sequence boundary data body based on the earthquake.
14. The apparatus of claim 9, wherein the fusion processing module is further configured to:
performing reverse processing on the gamma curve at the target well point to obtain a reverse gamma curve;
performing trending treatment on the reverse gamma curve to obtain a trended gamma curve;
and (3) removing the base line of the gamma curve after trending treatment to obtain a gamma curve reflecting the boundary of the high-frequency sequence.
15. The apparatus of claim 9, wherein the fusion processing module is further configured to:
And performing baseline removal treatment on the porosity curve at the target well point to obtain a porosity curve reflecting the boundary of the high-frequency sequence.
16. The apparatus of claim 9, wherein the fusion processing module is specifically configured to:
discretizing to form a plurality of column data points by taking the third-order boundary curve based on the earthquake as a basic curve, discretizing the gamma curve reflecting the high-frequency sequence boundary to form a plurality of column data points after normalization treatment, superposing the column data points on a plurality of column data points corresponding to the third-order boundary curve based on the earthquake of the corresponding depth point, and fusing the column data points into a fourth high-frequency sequence boundary curve based on the earthquake;
discretizing to form a plurality of column data points by taking a fourth time sequence boundary curve based on the earthquake as a basic curve, discretizing to form a plurality of column data points after carrying out normalization processing on a porosity curve reflecting a high-frequency sequence boundary, superposing the column data points on a plurality of column data points corresponding to the fourth time sequence boundary curve based on the earthquake of a corresponding depth point, and fusing the column data points into a fifth high-frequency sequence boundary curve based on the earthquake;
discretizing a carbonate particle curve reflecting a high-frequency sequence boundary into a plurality of column data points by taking a fifth-order sequence boundary curve based on the earthquake as a basic curve, discretizing the carbonate particle curve reflecting the high-frequency sequence boundary into a plurality of column data points after normalization treatment, and then superposing the column data points on a plurality of column data points corresponding to the fifth-order sequence boundary curve based on the earthquake of a corresponding depth point to fuse the column data points into a sixth high-frequency sequence boundary curve based on the earthquake; wherein the carbonate particle curve reflecting the high frequency sequence boundary is a curve formed by quantifying carbonate particles into a plurality of column data points from granular limestone to argillaceous limestone;
Discretizing a carbonate texture curve reflecting a high-frequency sequence boundary into a plurality of column data points by taking a sixth-order sequence boundary curve based on the earthquake as a basic curve, discretizing the carbonate texture curve reflecting the high-frequency sequence boundary into a plurality of column data points after normalization treatment, and then superposing the column data points on a plurality of column data points corresponding to the sixth-order sequence boundary curve based on the earthquake of the corresponding depth point to fuse the column data points into a seventh high-frequency sequence boundary curve based on the earthquake; wherein, the carbonate rock texture curve reflecting the high-frequency sequence boundary is a curve formed by quantifying the rock texture structure of the carbonate rock into a plurality of column data points;
discretizing a series of data points by taking a seventh layer sequence boundary curve based on the earthquake as a basic curve, discretizing a suture line frequency curve of carbonate rock reflecting a high-frequency layer sequence boundary into a plurality of series of data points after normalization treatment, superposing the series of data points on a plurality of series of data points corresponding to the seventh layer sequence boundary curve based on the earthquake of a corresponding depth point, and fusing the series of data points into an eighth high-frequency layer sequence boundary curve based on the earthquake; wherein, the suture frequency curve of the carbonate rock reflecting the high-frequency sequence boundary is a curve formed by quantifying the suture frequency of the carbonate rock into a plurality of column data points;
Discretizing to form a plurality of column data points by taking an eighth sequence boundary curve based on the earthquake as a basic curve, discretizing to form a plurality of column data points after normalizing a carbonate rock asphalt content curve reflecting the sequence boundary, and then superposing the column data points on a plurality of column data points corresponding to the eighth sequence boundary curve based on the earthquake of the corresponding depth points to fuse the column data points into a ninth high-frequency sequence boundary curve based on the earthquake; wherein, the asphalt content curve of the carbonate rock reflecting the layer sequence boundary is a curve formed by quantifying the asphalt content of the carbonate rock into a plurality of column data points;
discretizing to form a plurality of column data points by taking a ninth-order layer sequence boundary curve based on the earthquake as a basic curve, discretizing to form a plurality of column data points after carrying out normalization treatment on a dolomite content curve of carbonate rock reflecting the layer sequence boundary, superposing the column data points on a plurality of column data points corresponding to the ninth-order layer sequence boundary curve based on the earthquake of a corresponding depth point, and fusing the column data points into a tenth high-frequency layer sequence boundary curve based on the earthquake; wherein, the dolomite content curve of the carbonate rock reflecting the sequence boundary is a curve formed by quantifying the dolomite to limestone content of the carbonate rock into a plurality of column data points.
17. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method of any of claims 1 to 8 when executing the computer program.
18. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program which, when executed by a processor, implements the method of any of claims 1 to 8.
19. A computer program product, characterized in that the computer program product comprises a computer program which, when executed by a processor, implements the method of any of claims 1 to 8.
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2025123642A1 (en) * 2023-12-15 2025-06-19 中国石油天然气股份有限公司 Method and apparatus for determining sequence boundaries in high-frequency seismic sequence stratigraphy

Family Cites Families (7)

* Cited by examiner, † Cited by third party
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US6424918B1 (en) * 1999-04-02 2002-07-23 Conoco Inc. Method for integrating gravity and magnetic inversion data with model based seismic data for oil, gas and mineral exploration and production
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CN109143399B (en) * 2017-06-28 2021-11-09 中国石油化工股份有限公司 Method for identifying carbonate rock sequence interface
CN110954951B (en) * 2019-11-25 2021-01-26 中国石油大学(华东) Method for dividing and identifying four-level sequence stratum by using seismic slice
CN113885096B (en) * 2020-07-01 2024-07-23 中国石油化工股份有限公司 High-frequency layer sequence division and small layer comparison method and device, electronic equipment and medium
CN115166824B (en) * 2022-06-29 2024-12-20 中海石油(中国)有限公司 Characterization method of reservoir architecture boundary types of sublacustrine fans constrained by sequence stratigraphic framework
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