Numerical Models for Low-Permeability Reservoir Characterization
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Solution Overview
Problem
In low-permeability oil reservoirs, conventional pressure-transient analysis faces challenges due to insufficient data from short build-up or fall-off tests, often requiring a priori knowledge of flow capacity, which is unavailable, especially in exploration wells, leading to uncertainty in data analysis.
Innovation Solution
The use of numerical models that simulate well production using reservoir and well data, allowing for the characterization of low-permeability reservoirs without prior knowledge of flow capacity, by iteratively adjusting model properties to match pressure and derivative data from short-time well tests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional pressure-transient analysis is used with short build-up or fall-off tests, then the analysis can be performed with available data, but the reliability of the analysis deteriorates due to insufficient data and unknown flow capacity
Solution Approach 1:
A numerical model is introduced as an intermediary between the well test data and the reservoir characterization results. The numerical model incorporates geological knowledge, well configuration, and reservoir physics to bridge the gap between limited test data and reliable reservoir parameters, allowing analysis without requiring full radial flow regime data
Solution Approach 2:
The numerical model is prepared in advance with pre-defined geological frameworks, well configurations, and reservoir physics before the well test. This preliminary setup allows the model to interpret short-duration test data more effectively by providing context and constraints that guide the interpretation toward reliable results
2Device complexity
If a priori knowledge of flow capacity is required for conventional transient analysis, then the analysis framework is simplified, but the adaptability to exploration wells deteriorates when flow capacity is unavailable
Solution Approach 1:
The numerical model dynamically adjusts reservoir parameters and flow capacity estimates during the matching process rather than requiring fixed a priori values. The model iteratively refines its understanding of flow capacity by comparing simulated pressure responses with actual test data, allowing it to adapt to exploration wells where flow capacity is unknown
Solution Approach 2:
The numerical model treats flow capacity as a variable parameter that can be optimized during the matching process rather than a fixed input. By changing and adjusting parameters like permeability, porosity, and flow capacity iteratively, the model can characterize exploration wells without requiring pre-known flow capacity values
3Measurement precision
If long build-up tests are conducted to obtain sufficient data, then the data quality improves, but the loss of production and expense increase
Solution Approach 1:
The numerical model achieves reliable reservoir characterization using only a partial duration of the build-up test (short-time data) rather than requiring the full long-duration test. By applying sophisticated numerical matching techniques to the available short-duration data, the model extracts maximum information without needing excessive test time, thereby reducing production loss and expense
Data Source
AI summary
Systems and methods include a computer-implemented method for characterizing low-permeability reservoirs by using numerical models. A numerical model modeling production of a well is prepared using reservoir data and well data. The numerical model is updated, including adjusting numerical model properties, until results of performing a quality assurance/quality control check indicate that the numerical model is within acceptable limits. Pressure derivatives are extracted from a transient test to create a functional numerical model. Simulations are run on the functional numerical model and reservoir features and properties are adjusted until acceptable results are achieved on: 1) a pressure match between pressures modeled in the functional numerical model and transient pressures of the well, and 2) a log-log plot derivative match between a pressure derivative of the functional numerical model and a pressure derivative of the transient pressures of the well. A simulation output that is based on the simulations is provided.