Permian Carbonate Porosity Prediction Using Quantum Resonance Interferometry Processing

Gulati, Arushi ^*1; Bogdan, Robert ²
(1) R&D, Vialogy, Pasadena, CA.
(2) Geophysical Services, ViaLogy, Pasadena, CA.

Porosity prediction is at the heart of discriminating potentially productive carbonate bodies. Pre-stack inversions are challenged by Permian Carbonate geometries as they are often below the well log or seismic reflection resolution. This paper presents a novel approach to porosity prediction using nonlinear signal processing. Unlike structural faulted traps, Permian carbonates represent a stratigraphic formation with discontinuities over small areas. Because of the broad-spectrum of diagenesis that affects these rocks, the final porosity in carbonates may or may not be related to depositional environment. So basin geology provides limited insight to positioning individual wells. Also, unlike other lithologies, the original primary porosity in carbonates may be totally destroyed during diagenesis and significant new secondary porosity may be created. Quantum Resonance Interferometry (QRI) processing exploits the full seismic acquisition spectrum to assess how low frequency and high-frequency noise is differentially and directly modulated by different types of porosity. QRI leverages advances in reservoir geophysics that have described how reservoirs act to scatter seismic waves because of the high complex impedance contrast and higher attenuation compared to the surrounding rocks with little attenuation. This paper presents three cases studies where QRI signal processing technique is applied to carbonate porosity assessment in three different Permian prospects - Wolfcamp laminates, detritus, fractured Strawn and dolomitized shelf carbonate. The three reservoirs are complex, slope and basin systems, including debris flows, grain flows and turbidites. The Wolfcamp is comprised of a sequence of basinal, interbedded shales and carbonates. Results are presented to show how calibration curves can be derived using well control zones of interest, to relate log values of effective carbonate porosity to output of QRI nonlinear engine, and seismic amplitude. These porosity curves are then applied to predict porosity away from the well-bore. Testing with blinded wells show R2 between predicted and ground-truth values of over 70% for boreholes that are 2 to 3miles away from the training wells. Also, extensive benchmarking is presented to compare performance of the method in fractured and unfractured carbonates.