Resistivity Logging Inversion Using Statistical Distribution Filtering
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Solution Overview
Problem
Deep resistivity logging tools face challenges in accurately inverting formation models due to local minima issues and solution ambiguity, especially when dealing with large depth ranges, resulting in multiple formation modes that fit within a certain misfit threshold, leading to unreliable inversion results.
Innovation Solution
A method involving a distance-to-bed-boundary (DTBB) inversion algorithm and post-processing schemes, including generating a statistical distribution of formation parameters using histograms to filter and select dominant inversion solutions, thereby generating a reliable formation model that summarizes inversion solutions and aids in identifying formation layers and wellbore trajectories.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Length of stationary object
If deep resistivity logging tools are used to detect formation boundaries at large depth ranges (100 feet), then the detection range is improved, but the inversion process suffers from local minima issues and solution ambiguity
Solution Approach 1:
The patent applies preliminary action by performing a qualitative correlation method before the quantitative inversion process. The DTBB algorithm first identifies formation boundaries qualitatively using well logs and seismic data, establishing an initial formation model that serves as a informed starting point for the subsequent inversion process, thereby avoiding local minima traps
Solution Approach 2:
The patent uses an intermediary approach by introducing a qualitative DTBB inversion algorithm as a mediator between the raw deep resistivity measurements and the final formation model. This intermediary step provides a physically meaningful initial guess that guides the quantitative inversion process, reducing solution ambiguity while maintaining the benefits of deep detection
2Reliability
If multiple initial guesses are used to explore all solution possibilities in inversion, then the reliability of finding the global minimum is improved, but the computational complexity and time increase
Solution Approach 1:
The patent reduces inversion process complexity by performing preliminary qualitative analysis using the DTBB algorithm to establish an informed initial formation model. This preliminary action provides a physically meaningful starting point that guides the quantitative inversion, reducing the need for multiple random initial guesses and thereby lowering computational complexity while maintaining solution confidence
Solution Approach 2:
The patent segments the inversion process into two distinct stages: (1) qualitative DTBB inversion using well logs and seismic data to identify formation boundaries, and (2) quantitative inversion using deep resistivity measurements. This segmentation allows each stage to use appropriate methods and initial conditions, reducing overall computational complexity while improving reliability
3Device complexity
If conventional resistivity logging tools are used, then the inversion process is simpler, but the detection range is limited to around 10 feet
Solution Approach 1:
The patent uses the DTBB algorithm as an intermediary that bridges conventional inversion methods with deep formation detection. By incorporating well logs and seismic data through this intermediary qualitative step, the system can handle deep resistivity measurements (100 feet detection range) that would otherwise be too complex for conventional inversion, thus extending detection range while managing complexity
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach effectively filters through hundreds of inversion solutions to identify meaningful and confident formation models, reducing ambiguity and improving the accuracy of formation layer identification and wellbore trajectory planning, enhancing the ability to steer drill bits towards hydrocarbon-producing zones.
Implementation Method 1
the resistivity tool, which includes one or more antennas for receiving a formation response and may include one or more antennas for transmitting an electromagnetic signal into the formation. When operated at low frequencies, the resistivity tool may be called an induction tool
Data Source
AI summary
A system and method of evaluating a subterranean earth formation using a statistical distribution of formation data. The system comprises a logging tool and a processor in communication with the logging tool. The logging tool comprises a sensor operable to measure formation data and is locatable in a wellbore intersecting the subterranean earth formation. The processor is operable to calculate inversion solutions to the formation data, wherein each inversion solution comprises values for a parameter of the formation, and generate a statistical distribution of the parameter along one or more depths in the subterranean earth formation using the inversion solutions. The processor is also operable to identify peaks within the statistical distribution and select the inversion solutions corresponding to the identified peaks, generate a formation model using the selected inversion solutions; and evaluate the formation using the formation model to identify formation layers for producing a formation fluid.