At RSI, reservoir characterization is conducted within our rock physics framework.
At RSI, reservoir characterization is conducted within our rock physics framework. Seismic data is often conditioned for structural and stratigraphic interpretation, and may not be appropriate for detailed quantitative interpretation. Our seismic data conditioning services pre-condition data to optimize the quality of pre- and post-stack data for later use in inversion, AVO and seismic attribute analysis to ensure the best results are achieved given the input data available.
In Solid Seismic, we use our customizable workflows to thoroughly investigate the relationships between the underlying rock and fluid properties and the measured seismic response prior to inversion. Our rock physics models are used to calibrate impedance and facies models to rock and fluid properties enabling the results of advanced seismic inversion to be tied to lithology and reservoir content. The results reliably predict properties of existing and future wells.
Solid Seismic projects may range in size and complexity from modeling and sensitivity analysis around a single well, to complete multi-well, 3-D reservoir characterization programs. Depending upon client choice, we typically provide rock-physics and seismic models, seismic data pre-conditioning, pre- or post-stack inversion, seismic facies modeling and lithology and fluid prediction.
Solid reservoir characterization begins with thorough data analysis. If you get the rocks and rock physics wrong, the seismic characterization will be wrong. We don’t. We’re Rock Solid.
Most seismic data is processed to optimize image quality for structural and stratigraphic interpretation, with little regard to preserving characteristics essential for successful seismic reservoir characterization. No matter how sophisticated the inversion algorithm, use of inadequately processed seismic data will severely impact the quality of the final interpretation.
At RSI we believe that optimizing the quality of the data input to the interpretation process ensures a robust outcome. We use a comprehensive toolkit to provide a complete suite of seismic data conditioning steps to optimize the quality of pre- and post-stack seismic data prior to use in impedance, AVO and seismic facies analysis applications. We also use our Geophysical Well Log Analysis to condition well logs used for seismic modeling along with well tie analysis. Our toolkit may be applied to pre- or post-stack seismic data and involves several interlinked steps.
In all of our integrated services, our goal is to offer the greatest understanding of the depositional environment, so that decisions can be made with confidence.
For seismic inversion, we use a pre-stack constrained stratigraphic inversion algorithm developed by IFP and consortium members for simultaneously extracting elastic properties from amplitude versus angle (AVA) information.
The inversion is a 3D model-based algorithm, inverting multiple angle stacks simultaneously to yield P- and S-wave impedance volumes and an optional density volume. Signal-to-noise ratios in the seismic data and parameter uncertainties can be incorporated directly into the inversion, minimizing error in the results.
We also use geological constraints to control of the confidence in each parameter and the lateral continuity of the resulting structure with a stronger correlation in the bed-parallel direction. The constraining models are created from structural frameworks, well logs, and geostatistical methods.
We also use geological constraints to control of the confidence in each parameter (e.g. impedance or density), and the lateral continuity of the resulting structure with a stronger correlation in the bed-parallel direction. The constraining models are created from structural frameworks, well logs, and geostatistical methods.
Rock physics transforms developed during the well log analysis and seismic modeling phases can be applied to the resulting impedance volumes to provide quantitative measures of reservoir properties such as clay content, saturation and porosity.
The result is a unique and powerful inversion formulation ensuring optimum results under a variety of geological and petro physical/rock physics scenarios.
As part of our integrated services, we offer clients a full complement of pre-stack (AVO/AVA) and post-stack seismic attributes. AVO/AVA and post-stack seismic attributes are generated to drive seismic facies analysis, used in areas without well control where seismic inversion is not feasible and are used to complement seismic inversion results in areas where well log calibration is possible. In most cases, it is possible to establish a relationship between these seismic attributes and changes in the rock properties for example sand presence and porosity.
Seismic Facies Classification
We also offer a multi-attribute neural network workflow, designed to provide supervised or unsupervised seismic facies descriptions calibrated to well data. These seismic facies may be related to geometrical characteristic of the reservoir such as faults or fractures, or directly to a rock properties like porosity and/or reservoir content.