Ultra-Deep Resistivity Inversion for Reservoir Property Accuracy
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Solution Overview
Problem
Existing geo-steering systems face challenges in accurately interpreting ultra-deep resistivity data due to ambiguities caused by formation rock properties like density and porosity, leading to incorrect steering decisions and potential bypassing of hydrocarbon-bearing zones.
Innovation Solution
Integration of ultra-deep resistivity measurements with other sensor data using a joint cross-property inversion algorithm to generate real-time or near real-time reservoir properties, such as porosity and fluid saturation, through a rock physics forward model and inversion algorithm.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Length of stationary object
If ultra-deep resistivity data is used alone for geo-steering interpretation, then measurement depth is improved, but measurement precision deteriorates due to ambiguities from rock properties
Solution Approach 1:
The patent combines ultra-deep resistivity measurements with other sensor measurements (such as acoustic, density, or neutron porosity measurements) to jointly interpret formation properties. This merging of multiple measurement types allows the system to overcome the ambiguities inherent in using resistivity data alone, thereby improving interpretation accuracy while maintaining the advantage of deep measurement depth.
2Device complexity
If conventional resistivity tools are used, then device complexity is reduced, but measurement depth is limited
Solution Approach 1:
The patent employs a multi-functional measurement system that integrates ultra-deep resistivity capabilities with other formation evaluation functions in a single tool assembly. This allows the device to perform multiple types of measurements (resistivity, acoustic, density, etc.) simultaneously, achieving deep measurement depth without proportionally increasing device complexity, as the same tool platform serves multiple purposes.
3Measurement precision
If multiple sensor measurements are integrated, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent divides the measurement and processing system into modular segments, where each sensor type (resistivity, acoustic, density) operates as an independent measurement module. The data processing is also segmented into separate analysis streams that are later integrated. This segmentation allows for improved measurement precision through multiple sensors while managing device complexity through modular design, making the system more maintainable and adaptable.
Data Source
AI summary
The disclosure presents processes to receive at least one set of ultra-deep resistivity data, and at least one additional set of measurements. The set of measurements can be resistivity data or other sensor measurements, for example, nuclear, magnetic resonance, seismic, acoustic, temperature, or pressure. The set of measurements can be data for which a relationship between the formation values and the formation porosity or fluid saturation exists. For example, acoustic or seismic compressional velocity, shear velocity, density or a ratio thereof such as acoustic impedance, compressional wave (vp)/shear wave (vs) velocity ratio, or other relationships. The processes can identify rock physics forward models to utilize as well as respective constitutive equations. Various inversion algorithms can be applied to the resistivity data and set of measurements to generate an inversion output. The inversion output can be utilized to determine subterranean formation characteristics, such as porosity, density, or fluid saturation.