Borehole Imager Tool Mud Property Determination
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Solution Overview
Problem
Current borehole imager tools lack the capability to accurately determine oil-based mud properties, which are necessary to estimate formation resistivity and permittivity, as they do not have a mud cell to measure these properties during downhole operations.
Innovation Solution
A system and method that utilize multi-frequency measurement data and physical borehole information to determine oil-based mud properties, allowing for the removal of mud effects from measurement data to obtain accurate formation resistivity and permittivity images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a mud cell is added to the borehole imager tool to directly measure mud properties, then measurement precision of mud properties is improved, but device complexity increases
Solution Approach 1:
The patent uses existing measurement data from the borehole imager tool as an intermediary to indirectly determine mud properties. Instead of directly measuring mud properties with a dedicated mud cell, the system uses formation resistivity and permittivity measurements already being taken by the imager tool, and processes this data through an inversion algorithm to derive mud properties. This intermediary approach allows obtaining mud property information without adding direct measurement hardware.
Solution Approach 2:
The borehole imager tool performs dual functionality: it measures formation properties for imaging purposes while simultaneously using its own measurement data to determine mud properties. The tool serves itself by utilizing its existing measurement capabilities and processing resources to extract additional information (mud properties) from the data it already collects, eliminating the need for separate dedicated measurement devices.
2Measurement precision
If multi-frequency measurement data is processed through inversion algorithms to determine mud properties, then mud properties determination accuracy is improved, but processing time and computational complexity increase
Solution Approach 1:
The system performs preliminary processing of multi-frequency measurement data by organizing it into a structured format and preparing the inversion algorithm with pre-defined models of formation and mud electrical properties. The measurement data is pre-processed to separate formation contributions from mud contributions before the actual inversion calculation, reducing the computational burden during the time-critical processing phase.
Solution Approach 2:
The inversion algorithm varies electrical property parameters (resistivity and permittivity) across different frequency points to match the multi-frequency measurement data. By changing these parameters systematically and comparing predicted responses with actual measurements, the algorithm converges on accurate mud property values. This parameter-based approach allows efficient processing of multi-frequency data through iterative optimization rather than complex time-domain simulations.
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
Enables the production of high-resolution resistivity images that accurately depict subsurface structures, improving reservoir characterization and identifying thin beds, fractures, and other fine features by accounting for mud properties in the imaging process.
Implementation Method 1
These borehole imager tools may provide a resistivity image of the formation immediately surrounding the borehole. Generally, the imager tool forms a resistivity image from multi-frequency measurement data.
Implementation Method 2
A cost function may be minimized during an inversion to determine a set of oil-based mud properties that include a mud resistivity and a relative permittivity of the oil-based mud.
Data Source
AI summary
A method for determining mud properties may comprise taking multi-frequency measurement data with a downhole tool, selecting an injector electrode from the one or more injector electrodes for the multi-frequency measurement data, selecting data from the multi-frequency measurement data with low resistivity or a large standoff, creating a forward model based at least partially on the selected data by making initial guesses of model parameters for one or more mud properties, performing a cost function minimization with the forward model, identifying from the cost function minimization if a misfit is above or below a threshold, and identifying the one or more mud properties based at least in part on the cost function minimization. A system may comprise a downhole tool including a mandrel, one or more arms, one or more pads, and one or more injector electrodes. The system may further include an information handling system.