--> Abstract: Land Seismic Data Regularization: Overcoming Urban Acquisition Limitations, by Roy Burnstad and Abdulrahim A. Al-Mubarak; #90105 (2010)

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AAPG GEO 2010 Middle East
Geoscience Conference & Exhibition
Innovative Geoscience Solutions – Meeting Hydrocarbon Demand in Changing Times
March 7-10, 2010 – Manama, Bahrain

Land Seismic Data Regularization: Overcoming Urban Acquisition Limitations

Roy Burnstad1; Abdulrahim A. Al-Mubarak2

(1) EXPEC ARC, Saudi Aramco, Dhahran, Saudi Arabia.

(2) AED, Saudi Aramco, Dhahran, Saudi Arabia.

Prior to future reservoir development, Saudi Aramco embarked on an urban 3D seismic data acquisition project over the Dammam oil field located in the Eastern Province of Saudi Arabia. As expected, the 250 km2 vibroseis survey proved to be a processing challenge. Field data quality was impacted by (1) an outcropping hard layer with extensive faulting and fracturing from reservoir to surface, (2) restricted source size and access within urban areas, (3) variable receiver array dimensions within urban areas, (4) high levels of source generated, scattered and cultural noise, and (5) complex near surface geology. It soon became apparent that irregular positioning of source locations throughout urban areas meant noise suppression procedures could only be applied in two dimensions. To implement more powerful three dimensional filtering, a solution for irregular source positioning became the central issue. Extensive testing resulted in an innovative data regularization workflow designed to proceed 3D noise filtering.

Initial processing steps using standard noise removal techniques were unable to produce an interpretable volume. A number of pre-stack custom techniques, such as frequency domain median filtering and frequency-distance deconvolution, were then implemented. Unfortunately, pre-stack time migration stacked images continued to be disappointing. A study was convened to identify underlying reasons for the failure of post-stack images when noise suppression appeared to work pre-stack. A data regularization workflow to allow 3D noise suppression was identified as the best solution. Comparison of post-stack images proved fault details could be imaged, thus providing a usable 3D volume for field development.