Repeatability of 3‐D ocean bottom cable seismic surveys

Beasley, Craig J.; Chambers, Ron; Workman, Rick; Craft, Kenneth L.; Meister, Laurent

doi:10.1190/1.1826559

Cited by 3 publications

(3 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…); different source waveforms or shooting directions; different receiver hardware or deployment methods; positioning errors for source and receiver locations, including cable feather; different acquisition crews and equipment; and changing near-surface conditions (weather, water table, tides, ambient noise, etc.). Published case studies of repeatability under controlled conditions (Beasley et al, 1997;Rennie et al, 1997;Porter-Hirsche and Hirsche, 1998) demonstrate the potential impact of acquisition differences on seismic repeatability.…”

Section: Nonrepeatability Of Seismic Reflection Experimentsmentioning

confidence: 97%

Cross‐equalization data processing for time‐lapse seismic reservoir monitoring: A case study from the Gulf of Mexico

2001

View full text Add to dashboard Cite

Nonrepeatable noise, caused by differences in vintages of seismic acquisition and processing, can often make comparison and interpretation of time-lapse 3-D seismic data sets for reservoir monitoring misleading or futile. In this Gulf of Mexico case study, the major causes of nonrepeatable noise in the data sets are the result of differences in survey acquisition geometry and binning, temporal and spatial amplitude gain, wavelet bandwidth and phase, differential static time shifts, and relative mispositioning of imaged reflection events. We attenuate these acquisition and processing differences by developing and applying a cross-equalization data processing flow for time-lapse seismic data. The cross-equalization flow consists of regridding the two data sets to a common grid; applying a space and time-variant amplitude envelope balance; applying a first pass of matched filter corrections for global amplitude, bandwidth, phase and static shift corrections, followed by a dynamic warp to align mispositioned events; and, finally, running a second pass of constrained space-variant matched filter operators. Difference sections obtained by subtracting the two data sets after each step of the cross-equalization processing flow show a progressive reduction of nonrepeatable noise and a simultaneous improvement in timelapse reservoir signal.

show abstract

Section: Nonrepeatability Of Seismic Reflection Experimentsmentioning

confidence: 97%

Cross‐equalization data processing for time‐lapse seismic reservoir monitoring: A case study from the Gulf of Mexico

2001

View full text Add to dashboard Cite

show abstract

“…It is common to have unavoidable differences in acquisition geometry between repeated seismic surveys, differences in the source waveforms, differences in receiver responses or even differences not related to equipment, such as near surface conditions (wet versus dry near surface, tides, winds, etc.) (Beasley et al, 1997;Ross and Altan, 1997;Rennie et al, 1997;Porter-Hirsche and Hirsche, 1998). Other differences can arise from inconsistent processing of time-lapse data due to different processing software or personnel, advances in processing technologies, etc.…”

Section: Introductionmentioning

confidence: 99%

Surface-consistent matching filters for time-lapse seismic processing

Almutlaq

Margrave

2013

GEOPHYSICS

View full text Add to dashboard Cite

We evaluated the concept of surface-consistent matching filters for processing time-lapse seismic data, in which matching filters are convolutional filters that minimize the sum-squared error between two signals. Because in the Fourier domain a matching filter is the spectral ratio of the two signals, we extended the well-known surface-consistent hypothesis such that the data term is a trace-by-trace spectral ratio of two data sets instead of only one (i.e., surface-consistent deconvolution). To avoid unstable division of spectra, we computed the spectral ratios in the time domain by first designing trace-sequential, least-squares matching filters, then Fourier transforming them. A subsequent least-squares solution then factored the trace-sequential matching filters into four operators: two surface-consistent (source and receiver) and two subsurface-consistent (offset and midpoint). We evaluated a time-lapse synthetic data set with nonrepeatable acquisition parameters, complex near-surface geology, and a variable subsurface reservoir layer. We computed the four-operator surface-consistent matching filters from two surveys, baseline and monitor, then applied these matching filters to the monitor survey to match it to the baseline survey over a temporal window where changes were not expected. This algorithm significantly reduced the effect of most of the nonrepeatable parameters, such as differences in source strength, receiver coupling, wavelet bandwidth and phase, and static shifts. We computed the normalized root mean square difference on raw stacked data (baseline and monitor) and obtained a mean value of 70%. This value was significantly reduced after applying the 4C surface-consistent matching filters to about 13.6% computed from final stacks.

show abstract

“…Several repeatability studies have been performed to investigate crucial parameters controlling the NRMS level. Examples have been given by Beasley et al . (1997) on two‐dimensional (2D) ocean‐bottom‐cable data, by Ross and Altan (1997) on ocean‐bottom‐seismic data, by Landrø et al .…”

Section: Introductionmentioning

confidence: 99%

Overburden complexity and repeatability of seismic data: Impacts of positioning errors at the Oseberg field, North Sea

Misaghi¹,

Landrø²,

Petersen³

2007

Geophysical Prospecting

View full text Add to dashboard Cite

Repeatability of seismic data plays a crucial role in time‐lapse seismic analysis. There are several factors that can decrease the repeatability, such as positioning errors, varying tide, source variations, velocity changes in the water layer (marine data) and undesired effects of various processing steps. In this work, the complexity of overburden structure, as an inherent parameter that can affect the repeatability, is studied. A multi‐azimuth three‐dimensional vertical‐seismic‐profiling data set with 10 000 shots is used to study the relationship between overburden structure and repeatability of seismic data. In most repeatability studies, two data sets are compared, but here a single data set has been used because a significant proportion of the 10 000 shots are so close to each other that a repeatability versus positioning error is possible. We find that the repeatability decreases by a factor of approximately 2 under an overburden lens. Furthermore, we find that the X‐ and Y‐components have approximately the same sensitivity to positioning errors as the Z‐component (for the same events) in this three‐dimensional vertical‐seismic‐profiling experiment. This indicates that in an area with complex overburden, positioning errors between monitor and base seismic surveys are significantly more critical than outside such an area. This study is based on a three‐dimensional three‐component vertical‐seismic‐profiling data set from a North Sea reservoir and care should be taken when extrapolating these observations into a general four‐dimensional framework.

show abstract

Repeatability of 3‐D ocean bottom cable seismic surveys

Cited by 3 publications

References 4 publications

Cross‐equalization data processing for time‐lapse seismic reservoir monitoring: A case study from the Gulf of Mexico

Cross‐equalization data processing for time‐lapse seismic reservoir monitoring: A case study from the Gulf of Mexico

Surface-consistent matching filters for time-lapse seismic processing

Overburden complexity and repeatability of seismic data: Impacts of positioning errors at the Oseberg field, North Sea

Contact Info

Product

Resources

About