Permian Carbonate Porosity Prediction Using Quantum Resonance Interferometry Processing
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.
AAPG Search and Discovery Article #90142 © 2012 AAPG Annual Convention and Exhibition, April 22-25, 2012, Long Beach, California