3D seismic monitoring for enhancing thermal recovery

Eastwood, John; Anderson, D.B.; Boone, T.J.

doi:10.1190/1.1826598

Cited by 8 publications

(2 citation statements)

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“…Early case studies (Greaves and Fulp, 1987;Pullin et al, 1987 et al, 1992;Lumley, 1995;Eastwood et al, 1996) describe the seismic monitoring of fields undergoing thermally enhanced recovery processes such as steam flood or fireflood. Laboratory experiments (Wang and Nur, 1989) have shown temperature changes in reservoir conditions may induce extremely large velocity changes of up to 40%.…”

Section: Introductionmentioning

confidence: 99%

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

2001

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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.

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Section: Introductionmentioning

confidence: 99%

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

2001

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“…This pilot has evolved into the development of important seismic imaging tools for reservoir monitoring and production optimization (Eastwood et al 1994(Eastwood et al , 1996, which are currently being used at Imperial's in situ heavy oil properties. The ERCB also mandates a baseline 3D seismic survey before approving the development of any SAGD project.…”

Section: Impact Of Reservoir Heterogeneity On Thermal Recovery and Pementioning

confidence: 99%

Athabasca oil sands: reservoir characterization and its impact on thermal and mining opportunities

Peacock¹

2010

PGC

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The heavy oil deposits of Canada are a large resource with an estimated 1.7 Â 10 12 barrels of bitumen in place. The Lower Cretaceous McMurray Formation in the Athabasca area of northern Alberta contains about 900 Â 10 9 barrels of bitumen in place. This resource can be developed through surface mining and thermal in situ techniques. This paper examines the size of this resource in a global context and highlights its position relative to the North American market. The regional geology of the Western Canada Sedimentary Basin and the Athabasca area will also be reviewed. Understanding the regional reservoir distribution of the McMurray Formation is critical to understanding oil sands opportunities. Fluvial estuarine point bar reservoirs are a large portion of the resource that can be developed. Examples will be shown from the type outcrop location, where the stratigraphy can be organized into a hierarchy that subdivides channel-fills into bedsets, storeys, bars and barsets. Inclined heterolithic strata (IHS) surfaces can be identified. Considerable resource delineation drilling has occurred in the basin. The regulator for the Athabasca area specifies minimum drilling densities before project approvals are granted. Regional 2D seismic lines and project-specific 3D and 4D seismic datasets have also been acquired, to reduce the reservoir uncertainty and improve resource definition in this complex depositional environment. These techniques provide a unique opportunity to analyse a complex depositional system with abundant well and core control, outcrop data and seismic information.To determine preliminary deposition environments, software techniques have been successfully used to interpret large datasets quickly. Laser imaging of mine faces has also been used to record stratigraphy and determine the mined volume of ore. The importance of detailed reservoir characterization studies and their impact on thermal in situ recovery mechanisms will also be discussed. Understanding reservoir facies distributions and lateral relationships affects any recovery process, but has an even greater significance in a heavy oil reservoir.

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Nonrepeatable Noise Attenuation on Time-Lapse Prestack Data Using Fully Convolutional Neural Network and Masked Image-to-Image Translation Scheme

Lee,

Park,

Kim

et al. 2024

IEEE Trans. Geosci. Remote Sensing

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3D seismic monitoring for enhancing thermal recovery

Cited by 8 publications

References 0 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

Athabasca oil sands: reservoir characterization and its impact on thermal and mining opportunities

Nonrepeatable Noise Attenuation on Time-Lapse Prestack Data Using Fully Convolutional Neural Network and Masked Image-to-Image Translation Scheme

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