StatMod MC & RockMod Projects
Simultaneous Property and Lithology Simulation
Jason’s Markov Chain Monte Carlo (MCMC) geostatistical inversion is a powerful tool for separating individual lithologies and providing high-resolution models useful for identifying thin beds. It also produces multiple rock property models (e.g. lithology, porosity, permeability, BVHC, etc.), which can be used for prospect ranking and for output to geocellular models and reservoir flow simulators. StatMod® MC is the post-stack version of this technology, while RockMod® is the PreStack AVA/AVO version. The technology has proven itself both in carbonate areas and areas with tight sands.
MCMC technology is much better suited for inversion problems than sequential simulation-type algorithms, because it can take both the seismic and the geostatistics into account, simultaneously and rigorously, all the way through the process. The MCMC approach puts a rich, realistic model of the character of the reservoir (variograms, histograms, etc) together with a powerful seismic model (full- or pre-stack), and considers both simultaneously while searching for geologically plausible realizations. In effect, it constructs possible scenarios for the seismic with direct reference to the lithotypes, property crossplots, and spatial patterns which are believed to be present in the zone of interest.
The workflow for StatMod MC and RockMod® projects generally follow these steps:
- Load and condition seismic data (angle or offset gather stacks for RockMod), well logs, and velocity information
- Perform petrophysical and rock physics analysis on the well log data
- Estimate the seismic wavelet (for each angle or offset stack for RockMod projects) using a multi-well estimation technique
- Perform Property Simulation of the elastic parameters
- Run the MCMC inversion and QC the results
- Perform cosimulation to generate lithology, property, and statistics (P10, P50, P90, etc.) volumes.
- Analyze and interpret the results
In this West Texas carbonate case study, our client was having difficulty using the seismic data to identify and rank drilling locations (Figure at right). In fact, the client was not using the seismic at all and was simply drilling on a uniform grid.
Jason inverted the seismic for acoustic impedance and co-simulated for porosity. The next four wells, drilled based on the porosity volume, successfully encountered high porosity as predicted by the inversion. The porosity volumes also enabled fracturing in by-passed pay zones in existing wells, further increasing production.