The early integration of geological concepts and seismic (qualitative and quantitative) interpretation is a powerful tool to enhance the probability of success of an appraisal campaign. The presented example of an integrated workflow was applied to Perla Field (offshore Gulf of Venezuela), an Early Miocene carbonate reservoir containing gas and condensates. The work was therefore tailored on the integration of geological data and advanced seismic interpretation since exploration project start-up is a key to improve success of appraisal campaign and early production phases.
The presented case refers to an Early Miocene gas-bearing carbonate asset, Giant world-class reservoir. 3D Seismic data shows an isolated bank developed on basement high, thickness decreasing from crest-to-flanks. Wildcat well found 200m high-porous bio-GRST/PKST having moderate diagenetic imprint.
The red algae-dominated system formed low-angle ramps more than classical flat-top platforms. AVO attributes (Gradient) fully supported detailed seismic interpretation, since Carbonate reflections responded to elastic changes rather than subtle acoustic contrasts, negligible on conventional seismic. A petroelastic model and strict quantitative amplitude reliability were validated.
Acoustic Seismic inversion was performed right after the wildcat well.
Efforts devoted to realistic a-priori model building accounted for overburden trend and carbonate sequences velocity fields. The inversion results permitted seismic to effective porosity calibration (Seismic Pseudo-Porosity Volume), a significant tool for the delineation campaign.
Inversion properties vs depositional facies geometries relationships also allowed facies belts areal definition; jointly with structural attributes they were used to optimize the number, locations and trajectories of delineation wells. Appraisal wells confirmed the porosity predictions at seismic scale, and approach stability. No needs for acoustic inversion or calibration revision were considered, due to the high-quality blind tests results on appraisals. The availability of hard-data from extensive core campaign, re-enforced the geophysical calibration to reservoir facies, via petrophysics and rock-physics lab measures.
Seismic Porosity, Non-Supervised, and Supervised Facies cubes got into reservoir model, driving the areal distribution of Sw and K.
Elastic-Porosity large variability was tentatively correlated with the factor Gamma-K, representing the frame flexibility, hence pore structure of different sed-petro-facies.
Manipulation of Elastic Inversion data and more stable Rock Physics Model would be the next development to capture internal reservoir model microstructure variances.