Inverting for reservoir pressure change using time-lapse time strain: Application to Genesis Field, Gulf of Mexico

2007 ◽  
Vol 26 (5) ◽  
pp. 649-652 ◽  
Author(s):  
Neil Hodgson ◽  
Colin MacBeth ◽  
Luca Duranti ◽  
James Rickett ◽  
Kurt Nihei
2021 ◽  
Vol 135 (4) ◽  
pp. 36-39
Author(s):  
B. Z. Kazymov ◽  
◽  
K. K. Nasirova ◽  

A method is proposed for determining the distribution of reservoir pressure over time in a nonequilibrium-deformable gas reservoir in the case of real gas flow to the well under different technological conditions of well operation, taking into account the real properties of the gas and the reservoir.


2019 ◽  
Vol 38 (10) ◽  
pp. 754-761 ◽  
Author(s):  
Liqin Sang ◽  
Uwe Klein-Helmkamp ◽  
Andrew Cook ◽  
Juan R. Jimenez

Seismic direct hydrocarbon indicators (DHIs) are routinely used in the identification of hydrocarbon reservoirs and in the positioning of drilling targets. Understanding seismic amplitude reliability and character, including amplitude variation with offset (AVO), is key to correct interpretation of the DHI and to enable confident assessment of the commercial viability of the reservoir targets. In many cases, our interpretation is impeded by limited availability of data that are often less than perfect. Here, we present a seismic quantitative interpretation (QI) workflow that made the best out of imperfect data and managed to successfully derisk a multiwell drilling campaign in the Auger and Andros basins in the deepwater Gulf of Mexico. Data challenges included azimuthal illumination effects caused by the presence of the Auger salt dome, sand thickness below tuning, and long-term production effects that are hard to quantify without dedicated time-lapse seismic. In addition, seismic vintages with varying acquisition geometries led to different QI predictions that further complicated the interpretation story. Given these challenges, we implemented an amplitude derisking workflow that combined ray-based illumination assessments and prestack data observations to guide selection of the optimal seismic data set(s) for QI analysis. This was followed by forward modeling to quantify the fluid saturation and sand thickness effects on seismic amplitude. Combined with structural geology analysis of the well targets, this workflow succeeded in significantly reducing the risk of the proposed opportunities. The work also highlighted potential pitfalls in AVO interpretation, including AVO inversion for the characterization of reservoirs near salt, while providing a workflow for prestack amplitude quality control prior to inversion. The workflow is adaptable to specific target conditions and can be executed in a time-efficient manner. It has been applied to multiple infill well opportunities, but for simplicity reasons here, we demonstrate the application on a single well target.


2013 ◽  
Author(s):  
Zhu Zhenyu ◽  
Liu Zhipeng ◽  
Mi Fang ◽  
Sang Shuyun

2000 ◽  
Author(s):  
Xuri Huang ◽  
Robert Will ◽  
Mashiur Khan ◽  
Larry Stanley

2006 ◽  
Author(s):  
T. Hudson ◽  
B. Regel ◽  
J. Bretches ◽  
P. Condon ◽  
J. Rickett ◽  
...  

1999 ◽  
Author(s):  
J.J. Shyeh ◽  
D.H. Johnston ◽  
J.E. Eastwood ◽  
M. Khan ◽  
L.R. Stanley

Geophysics ◽  
2003 ◽  
Vol 68 (5) ◽  
pp. 1470-1484 ◽  
Author(s):  
Alastair M. Swanston ◽  
Peter B. Flemings ◽  
Joseph T. Comisky ◽  
Kevin D. Best

Two orthogonal preproduction seismic surveys and a regional seismic survey acquired after eight years of production from the Bullwinkle field (Green Canyon 65, Gulf of Mexico) reveal extraordinary seismic differences attributed to production‐induced changes in rock and fluid properties. Amplitude reduction (of up to 71%) occurs where production and log data show that water has replaced hydrocarbons as the oil–water contact moved upward. Separate normalizations of these surveys demonstrate that time‐lapse results are improved by using seismic surveys acquired in similar orientations; also, clearer difference images are obtained from comparing lower‐frequency data sets. Superior stratigraphic illumination in the dip‐oriented survey relative to the strike‐oriented surveys results in nongeological amplitude differences. This documents the danger of using dissimilar baseline and monitor surveys for time‐lapse studies.


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