Impact of seismic reprocessing with an emphasis on improving static errors corrections on 3-D land seismic data in Ellis Co., Kansas

Abstract

Seismic datasets play an important role in petroleum exploration and development in the mid- continent. The role of good quality seismic data processing of 3D seismic surveys cannot be underestimated, as it is foundational to the creation of reliable interpretation of seismic data. It is imperative that processing is done properly, as inaccurate data can cause a multitude of problems, from simply unusable data to dry holes drilled due to incorrect placement of seismic reflectors in the subsurface. This research focuses primarily on seismic time corrections “statics” problems with processing, as well as interpreting, a seismic horizon of interest. Specifically, this project investigates the impact of remaining static errors on the fidelity of the geometrical structural seismic attributes (i.e. amplitude) and evaluates the impact on seismic resolution. As this study shows, inaccurate static-correction processing of the seismic data can have a great impact on the overall success of exploratory drilling. Land seismic data of the midcontinent present unique static time-effects challenges that must be resolved. Among the most prominent are challenges posed by both topographic elevation statics, as elevation differences arising from differentially weathered carbonates and anhydrites in the near-surface, and velocity statics arising from near surface lateral velocity variations. These types of statics need to be removed to improve the overall quality of the processed seismic. When unresolved, these issues have a large negative effects on seismic amplitude and structural fidelity of the post-stack seismic datasets. This project developed a processing workflow specific to the challenges of seismic datasets in Kansas. An iterative process was used and the processing was highly tailored to deal with the residual statics affecting seismic horizons of rock formations surfaces seen in Kansas. These formations are primarily composed of carbonates and evaporites, and so greatly affect the static solutions needed. Mapped first arrival travel-times were used as the input for travel-time tomographic inversion, creating a velocity model of the near surface. Applying this to the original dataset improves the quality of the seismic cube and removes the obvious topographic imprint present in the original post-stack interpretation. An additional benefit of this workflow was a greatly increased signal-to-noise ratio and significantly improved seismic resolution. Interpretation of this reprocessed dataset more closely corresponds to well data in the area, giving a high level of confidence in the accuracy of the reprocessing workflow.