Synthetic Stratigraphic Column Reservoir Modeling
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Solution Overview
Problem
Current methods for reservoir characterization in the oil and gas industry face challenges in accurately estimating subsurface reservoir properties due to limited well data, inadequate low-frequency models, and inconsistencies in seismic data, which lead to poor estimates of high-frequency components and neglect the geological constraints of stratigraphic layering.
Innovation Solution
A novel method that uses geophysical, geological, and formation evaluation data to develop labeled synthetic stratigraphic columns based on depositional rules and sedimentary stacking patterns, allowing for dynamic assignment and matching of elastic properties to create improved reservoir models that honor geological and geophysical constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If impedance inversion is performed using sparse reflectivity model to compensate for lack of high frequencies, then high frequency components can be estimated, but the sparse reflectivity model becomes inconsistent with actual geological setting leading to poor estimates
Solution Approach 1:
The patent introduces a low-frequency model as an intermediary that bridges the gap between seismic data and geological reality. This low-frequency model, derived from well data and seismic interpretation, serves as a foundation that maintains geological consistency while enabling high-frequency component estimation through the impedance inversion process.
Solution Approach 2:
The patent changes the approach by not directly inverting seismic data for high frequencies, but instead first establishing a low-frequency impedance model with proper geological constraints, then using this as a basis for recovering high-frequency components. This parameter separation approach (low-frequency vs. high-frequency) resolves the inconsistency problem.
2Quantity of substance
If low frequency model is generated from well data and seismic interpretation, then low frequency components are available for inversion, but the low frequency model becomes inadequate where limited well data is available
Solution Approach 1:
The patent makes the low-frequency model generation process universal by incorporating both well data and seismic interpretation as complementary inputs. This multi-functional approach allows the system to generate adequate low-frequency models whether well data is abundant or sparse, as the seismic interpretation provides additional constraints and guidance.
Solution Approach 2:
The patent performs preliminary action by generating the low-frequency model before the impedance inversion process. This pre-established low-frequency model, derived from integrated well and seismic data, provides a geologically consistent foundation that guides the subsequent high-frequency recovery, ensuring adequacy even in sparse well situations.
3Productivity
If seismic data is inverted directly using sparseness constraint for acoustic impedance values, then inversion can be performed, but the process neglects geological constraints of stratigraphic layering
Solution Approach 1:
The patent performs preliminary action by incorporating geological constraints into the low-frequency model generation stage before inversion. By establishing a geologically consistent low-frequency impedance model that respects stratigraphic layering, the subsequent inversion process automatically inherits these geological constraints without requiring direct modification of the inversion algorithm itself.
Data Source
AI summary
The present invention incorporates the use of geophysical, geological and formation evaluation data to develop synthetic stratigraphic columns based on depositional rules and sedimentary stacking patterns. The present invention utilizes dynamic assignment and matching whereby the synthetic columns can be easily conformed throughout the reservation characterization process as geological data becomes available.