Method for processing seismic data

Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Earth science

Reexamination Certificate

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C702S017000

Reexamination Certificate

active

06651006

ABSTRACT:

CROSS REFERENCE TO RELATED APPLICATIONS
Applicants claim priority under 35 U.S.C. §119 of GERMAN Application No. 199 04 347.7, filed: Feb. 3, 1999. Applicants also claim priority under 35 U.S.C. §120 of PCT/DE00/00139, filed: Jan. 12, 2000. The international application under PCT article 21(2) was not published in English.
BACKGROUND OF THE INVENTION
The invention relates to a method for processing a seismic 2-D or 3-D measurement data set comprising a great number of seismic traces each comprising a series of data points occupied by amplitude values.
Methods for exploring seismic data are employed worldwide for the purpose of obtaining additional knowledge about the spread of subterranean geological structures in addition to information gathered from sunk drilling holes. Owing to the information obtained from seismic data it is often possible to dispense with further cost-intensive exploration drilling operations, or to restrict their number to a minimum.
Sensors (geophones/hydrophones) are employed in the seismic exploration of subterranean structures that are lined up one after the other (2-D-seismology), or which are receiving sound waves. Such waves are excited by a seismic source, for example by an explosive charge, vibratory excitement or air guns, and are partly reflected back to the surface by the beds of the earth. The waves are registered by the sensors on the surface and recorded in the form of time series. Such a time series represents the seismic energy received in the form of amplitude variations. It is digitally stored and consists of uniformly arranged data points (samples), which are characterized by the time and the associated amplitude values. Such a time series is referred to also as a seismic trace. The measurement series migrates over the area to be explored, so that a seismic 2-D profile is recorded with such an arrangement.
The goal of the subsequent processing operation is to suppress the noise, for example by batch processing, or with the help of filters employed in a targeted manner. The results so obtained are vertical profiles in which amplitudes and propagation times as well as attributes derived from amplitudes are represented that serve as the basis for further geological evaluation. The geological strata can be observed on a profile by lining up the amplitudes laterally.
If the data are recorded not only along a line but in a flat matrix, a three-dimensional data volume is obtained. In the case of the 3-D volume, an amplitude value is assigned to any desired point in the underground structure that is described, for example by Cartesian coordinates. The vertical direction is measured in time (sound propagation time).
Large amounts of data (several gigabytes) are collected in such a process, which are stored and subjected to processing before the actual interpretation is possible with respect to, for example further exploration of the subterranean structures. Such processes require comprehensive computer resources and software for processing and correcting the received signals. The result is a seismic volume in the form of a 3-D data set that represents physical properties of the explored subterranean structure in a seismic reproduction.
Any desired sections such as, for example vertical profiles and horizontal slices relating to different depths of exploratory drilling can be extracted from said data set, which are then interpreted by geophysicists and geologists in the further course of the exploration operation. As such interpretation of the seismic reproductions so obtained substantially comprises an optical correlation, attempts have been made to automate such reproductions through subjective interpretation depending on one or a number of interpreters.
A method for seismic data processing is known from WO 96/18915, by which a seismic 3-D volume is divided in a great number of horizontal slices that are vertically standing one on top of the other and spaced from each other, whereby at least one slice is divided in a multitude of cells. In this process, each cell has at least 3 trace sections, whereby the first and the second trace sections are arranged in a vertical plane in the direction of the profile (inline), and the third trace section with the first trace section is arranged in a vertical plane substantially perpendicular to the direction of the profile (crossline). A cross correlation is subsequently carried out between each two trace sections in the two vertical planes, which results in inline- and crossline-values that are dependent upon the inclination of the beds of the earth. Combining such values in one cell results in a coherence value for the cell that is assigned to a data point of the cell. The end result in turn is a 3-D data volume from which any desired sections can be extracted and represented.
A method and a device for seismic data processing by means of coherency characteristics is known from EP 0 832 442 A1. In said process, a seismic volume is divided in horizontal slices in a manner similar to the method employed in the aforementioned published document, and said slices are in turn divided in cells. Said cells have the shape of cubes in the simplest case. Based on the at least two trace sections present in a cell, a correlation matrix is formed representing in each case the sum of the differences between the inner and the outer products of the set of values based on the trace sections. The quotient based on the highest inherent value of the matrix and the sum of all inherent values is then computed as the measure for the coherence. A 3-D volume consisting of coherence values is subsequently obtained in turn as the result.
Furthermore, EP 0 796 442 A1 relates to a method and a device for seismic data processing, by which a coherence method is carried out that is based on a semblance analysis. In a manner that is similar to the one employed in conjunction with the two aforementioned methods, a seismic data volume is divided in at least one horizontal time slice and the latter is then divided in a great number of three-dimensional analysis cells, whereby each cell comprises two predetermined lateral directions that are perpendicular in relation to one another, and at least five seismic trace sections that are arranged therein next to each other. A semblance value of the trace sections present in the cell is assigned to the corresponding data point in the respective cell. In said conjunction, the semblance is a known measure for the correspondence among seismic trace sections. By searching various earth bed inclinations and directions, the incidence and the direction of incidence of the analyzed reflector are then determined based on the best coherence. The computed inclination data are subsequently displayed for each cell in addition to the semblance value as well.
The three evaluation methods specified above do in fact permit supporting the data interpretation in an automated manner; however, the higher objectivity in the interpretation achieved in that way is traded for substantial expenditure required for computing the seismic data.
An image processing method is known from the presentation of the DGMK Deutsche Wissenschaftliche Gesellschaft für Erdöl, Erdgas und Kohle e.V. [German Scientific Society for Oil, Natural Gas and Coal], Tagungsbericht [Proceedings] 9601 (1996) by C. HELLMICH, H. TRAPPE and J. FERTIG, which is titled “Bildverarbeitung seismischer Attribute und Geostatistik im Oberkarbon” [Image Processing of Seismic Attributes and Geostatistics in the Upper Carboniferous]. Said method permits a quantitative characterization of seismic representations and thus further interpretations of the lithology. Different image processing filters are employed in said process on amplitude charts, and the variations or the continuity of the local neighborhood are quantified. Said filters represent 2-D multi-trace filters, and the local environment surrounding a data point is evaluated with the help of such filters. Operators employed for said purpose include the entropy and the dispersion

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