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Abstract

Time-lapse seismic in a desert environment is a major geophysical challenge due to the complex and changing nature of the near surface that inhibits both imaging and data repeatability. In this study, the problem is further compounded by the injection of CO2 into a stiff carbonate reservoir which results in small changes in reservoir acoustic impedance. Therefore, a highly repeatable acquisition system was required to detect these weak 4D signals. A hybrid system using deep buried receivers and surface vibroseis sources was found to provide the optimum solution. Along with careful survey design and acquisition, a specialized data processing workflow was developed to overcome the challenges faced by single source, single receiver data. In particular, the stacking of neighboring shots in a process known as supergrouping is essential for the reduction of 4D noise. Using this system, highly repeatable data has been achieved with mean NRMS of 6% between dry season surveys separated by more than one year. This level of repeatability allows small variations that may be related to CO2 injection to be observed.

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/content/papers/10.3997/2214-4609.201701948
2017-08-28
2024-04-19
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http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.201701948
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