Processing Geophysicists Research Articles

Seismic Soundoff

In this episode, Andrew Geary speaks with Stephen Hill about his new book, Illustrated Seismic Processing, Volume 2: Preimaging. Hill shares why the authors decided to present the seismic processing topics in reverse order, tips for seismic interpreters and acquisition specialists who work alongside seismic processing geophysicists, and why seismic processing is both an art and a science. Hear the full episode at https://seg.org/podcast/post/12383 .

On Relative Precedence of Coherent and Random Noise Attenuation

Noise attenuation has always been a challenging affair for acquisition or processing geophysicist. The quality of final product and ease for application of next main phases of processing such as deconvolution, velocity analysis, residual statics computation, stacking and migration grossly depends on the way and amount, the noise is eliminated while keeping the signal preserved. This study is aimed at analyzing and recommending the relative precedence of attenuation steps for coherent and random noises. It is inferred, using field data examples that source related coherent noise be treated first for attenuation and the random noise next in the realm of seismic data processing steps.

SPS to Seismic Data Mapping: An AWK Script for Merging Field Geometry with Seismic Data

SPS (Shell Processing Support) files contain vital acquisition information and are standard input for merging field geometry with seismic data. These files are interrelated and must conform one another and the data as well for some of the prime fields. But on many occasions, it does not hold and requires user's massive efforts to rectify this correspondence. The best way to circumvent this problem is to automate the procedure through coding a script. With this concept, an AWK script is coded, which replenishes processing geophysicist's inventory with data mapped SPS files which can straight away be input for updating trace headers of seismic data.

Pitfalls in processing near-surface reflection-seismic data: Beware of static corrections and migration

Near-surface seismic data are a challenge to the processing geophysicist who is familiar only with handling seismic data for target depths larger than 200 to 400 m. Residual static-correction techniques and migration procedures are used routinely for processing deeper data and can destroy data quality in the near surface. Near-surface seismic presents unique problems in processing because it usually is of suboptimal quality and often is recorded in an environment characterized by complex geologic structures. In a presentation of three case histories, one shows less severe consequences, and the other two portray disastrous consequences caused by static corrections and migration not being applied correctly. Graphical examples document the limitations of the residual statics and migration procedures. However, the method of hybrid seismic surveying is a positive and generally applicable solution when dealing with data from the shallow subsurface.

Velocity versus Offset (VVO) Estimation Using Local Event Correlation and Its Application in Seismic Processing and Analysis

Conventional velocity analysis is usually done in a relatively spare grid, for instance every half kilometers, during the processing of seismic data. It is very laborious work and very subjective. To deliver an accurate velocity picking, processing geophysicists must have a good understanding of geological background of area being analyzed and experiences. Velocity errors often occur during picking. Proper quality control and checking are a must. A good and reliable velocity field is very important in seismic processing for achieving high-quality seismic images as well as for delivering an accurate depth conversion. The new method presented here, was developed to correct velocity errors automatically by means of residual velocity correction, and to produce an offset-dependent RMS velocity field at the same time. The method is data driven, based on the normal move out equation (NMO) and measuring the local even correlation between adjacent traces. The stacking velocity is derived simply by averaging the velocity field. The proposed method was tested on synthetic and real data examples with good result. The velocity field has certain characteristics related to hydrocarbon presence. Supriyono (2011 and 2012) developed a new DHI method using velocity gradient attributes by cross-plotting the velocity versus offset (VVO). The velocity gradient exhibits high anomalous values in the presence of gas.

4D PLANNING AND EXECUTION STRATEGIES FOR AUSTRALIAN RESERVOIR MONITORING PROJECTS

Time-lapse (4D) reservoir monitoring is in its infancy in Australia, but is on the verge of becoming a mainstream pursuit. We describe the 4D seismic acquisition and processing strategies that have been developed and proven elsewhere in the world, and customise those strategies for Australasian applications.We demonstrate how a multidisciplinary pursuit of real-time acquisition and processing Quality Control (QC) is an integral component of any 4D project. The acquisition and processing geophysicists must be able to understand all the factors contributing to the 4D seismic signal as they happen. Such an understanding can only arise through rigorous project QC and management using interactive visualisation technology. In turn, the production geologists and reservoir engineers will then receive 4D seismic products that can be robustly and confidently used for the construction of accurate reservoir models and the pursuit of reliable reservoir simulations and forecasts.

Seawater velocity variations and real-time reservoir monitoring

As industry moves toward exploring and producing in deeper water areas, the impact of velocity variations in the water layer will become more critical. Acquisition crews are very much aware of this phenomenon. For example it is known that large salinity variations caused by salt seabed outcrop or fresh river water dumping can introduce velocity contrasts strong enough to create a reflection in the water column (such as the 3 s brine reflection in the Orca Basin, Gulf of Mexico) or can affect the balance of towed streamers. On the other hand, this problem requires more careful examination than is currently being undertaken by processing geophysicists and interpreters: Only the issue of velocity variations between infill and original acquisitions has been studied (Wombell, 1997 and MacKay and Fried, 2002).

Altering offsets and azimuths—in a computer

For years, seismic processing geophysicists used dip moveout (DMO) to alter the acquisition geometry. Our industry has found many uses for DMO because it converts the timing of nonzero-offset data to the timing of zero-offset data. More recently, theoreticians created data mapping as a generalization of the principle behind DMO. Data mapping converts data obtained at an observed offset and azimuth to data at a new offset and/or azimuth. The precise derivation of the data mapping resides in an arduous solution of the wave equation. Thus, data mapping transformations may appear magical. This article provides a simple, geometric understanding of the data mapping transformation. Before turning to the more general 3-D case, we first present the 2-D case. For the 2-D case, data mapping transforms data obtained at one offset distance into data “observed” at a second offset distance. To understand this procedure, we will use one principle, one requirement, and two assumptions. The principle is linear superposition and the requirement is physical invariance. For conceptual convenience, we assume reflection coefficients do not change with offset, and we also assume a constant velocity earth. The principle of linear superposition simplifies our task. As shown in Figure 1, it allows us to construct any input data from a linear superposition of spikes or impulses. In addition, data-mapped output is a linear superposition of data-mapped spike responses. Consequently, we need to understand only the data-mapping operation on a single spike at an arbitrary location. Figure 1. Linear superposition simplifies data mapping. The physical invariance restriction is obvious—the earth does not change as a result of altering the acquisition offset. Likewise, our image of that earth should not change. Depth migration should image the same subsurface using either the original data or the offset-transformed data. The constant velocity assumption …

Accuracy and limitations of the near-offset P-wave NMO velocity estimation in transversely isotropic media

The accuracy and limitations of the near-offset P-wave NMO velocity estimation in transversely isotropic media have been studied using numerical and physical modelling studies. An expression for the near-offset P-wave NMO velocity for a single horizontal reflector in a vertically transversely isotropic layer has been previously obtained: vnmo=αo1+2δwhere αo and δ respectively represent the vertical P-wave velocity and the P-wave critical anisotropy at oblique angles. The above equation is presented as being valid for any degree of anisotropy. The accuracy of this expression is subject to practical testing in this paper.Single layered horizontal models were used to carry out the numerical modelling studies. A computer program that calculates P-wave NMO velocities in transversely isotropic media was used. This program uses the exact ray and phase velocity equations in generating velocity functions to be used in ray tracing and is known to give accurate results. Using the elastic parameters for measured anisotropy in sedimentary rocks, the near-offset NMO velocities are computed using our computer program and the above expression. The results obtained at varying degrees of P-wave anisotropy are compared. The degree of anisotropy varied from very weak to strong and contrasting velocity functions were used in numerical modelling simulations.Phenolite materials with contrasting velocity functions were used to simulate transversely isotropic media with vertical axes of symmetry in physical modelling tests. Experimental reflection data were collected and velocity analysis was conducted for near-offset traces, and the NMO velocity determined by the maximum stack response. The elastic parameters, αo, and δ, of the Phenolite materials were recovered by an iterative inversion of first arrival travel times. These parameters were used to estimate the nearoffset P-wave NMO velocity in Phenolite using the NMO expression and also with our computer program. The NMO velocities obtained from these two methods were compared to that obtained from velocity analysis of the experimental seismic data. These comparisons enabled the validity of the above expression in yielding an accurate P-wave NMO velocity to be tested, in the limit of small offsets.Numerical and physical modelling results obtained from this study indicate that the accuracy of the near-offset P-wave NMO equation depends on the nature and degree of anisotropy encountered in a given area, and is not valid for all degrees of P-wave anisotropy. Since this equation is commonly used in estimating the near-offset P-wave NMO velocity when processing seismic data acquired over anisotropic sedimentary basins, processing geophysicists should proceed with caution when using this equation.

Geophysicists, their migration and recruiting

We are all familiar with migration a la seismic processing; we know much less and have very few hard facts about the migration of members in our own profession. After recruiting a processing geophysicist in 1996, I became interested in this topic. To begin to understand the “statics” and “dynamics” of exploration geophysics, I tabulated the results of the recruitment and some statistics about SEG’s membership in 1995 and 1996 which I extracted from the May issues of The Leading Edge.

The relationship of pre-stack apparent velocity filtering to the symmetry of the CMP stack response

Wearing my processing geophysicist's hat, I, like others, often ask questions to which there appear to be no answers readily available. One such question that had re-occurred to me was 'what is the relationship between pre-stack apparent velocity filtering and the common midpoint (CMP) stack response?' The elements of any answer were roughly -potential reduction in spatial resolution; -reduction in coherent noise; -apparent velocity in common source or geophone space is twice that observed on the CMP stack. During the summer of 1983 Walt Lynn presented some material at Western Geophysical's London office (as part of a week long 'Wave Equation Update School' lecture course given by Jon F. C1aerbout) entitled 'Dip filtering for noise suppression'. Part of this graphical material demonstrated how apparent velocity filtering could be viewed in source-geophone space as removing ciearly definable parts of a pre-stack diffraction. Upon this basis the following text is an attempt to answer my question by doing three things: • Setting down the necessary equations. • Showing how certain symmetry conditions affect the CMP stack. • Computing synthetic examples. The text will consider a point scatterer in the subsurface, how it responds to the CMP method and what happens when pre-stack apparent velocity filtering is included. The most important conclusion will be that certain apparent velocity filter symmetry conditions are necessary if the CMP stack is to respond similarly to positive and negative dips. The analysis will commence by describing the prestack traveltime surface that is associated with the point scatterer, which is sometimes called Cheop's Pyramid. Equations for apparent velocity on the commonly used axes of Cheop's Pyramid will be derived which show how certain areas of the surface are rejected by apparent velocity discrimination. The idea of symmetry will be described and a set of rules will be presented in order to test whether the pre-stack apparent velocity filter will prejudice dip direction on the CMP stack. Some computed examples will be presented along with a brief description of the computational method used. Finally a potential problem with 'marine' three-dimensional (3D) surveys that can be caused by pre-stack apparent velocity filtering will be briefly discussed.

A Microcomputer Workstation for Interactive Geology and Geophysics: ABSTRACT

The capabilities of a new microcomputer system are reviewed. This system allows easy data management for both geologists and processing geophysicists. Currently available peripherals include a digitizer, pen plotter, raster graphics printer, and graphics video. Communications allow hardwired or modern access to other computers. End_Page 1704------------------------------ The application of software centers around a unified data management system and is extremely menu oriented, allowing easy use by personnel unfamiliar with computers. Applications software serves to assist in data acquisition, quality control, and computation for both seismic processing and interpretation. These applications include handling of such data as geometry, velocities, and muting, as well as geologic applications such as digitizing horizons, storing and plotting regional data, and digitizing and processing well log data. End_of_Article - Last_Page 1705------------