Borehole Correction for Formation Conductivity Measurement
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Solution Overview
Problem
Conventional resistivity tools face challenges in accurately determining formation conductivity due to borehole effects, particularly when conductive drilling muds are present, which complicate the interpretation of measurements and make it difficult to infer formation properties.
Innovation Solution
A method is developed to correct formation properties by obtaining voltage measurements using a logging tool in a borehole, determining a tensor for the formation, computing a borehole-inclusive modeled tensor, optimizing parameter values, and calculating a borehole-corrected tensor to remove the effects of the borehole and tool, thereby enabling the determination of accurate formation properties.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional induction tools are used to measure formation conductivity, then voltage measurements can be obtained from the earth formations, but the conductive drilling mud in the borehole contributes significantly to the received signals, making it difficult to accurately determine formation properties
Solution Approach 1:
The measured conductivity tensor is segmented into distinct components: borehole effects tensor and formation properties tensor. By mathematically separating these contributions, the method isolates the formation conductivity signal from the contaminating borehole effects, enabling accurate determination of formation properties despite the presence of conductive drilling mud.
Solution Approach 2:
A borehole-inclusive modeled tensor acts as an intermediary between the raw measurements and the formation properties. This modeled tensor incorporates known borehole parameters (mud conductivity, hole diameter, tool position) to represent and subsequently remove the borehole effects, serving as a mediator that facilitates the extraction of accurate formation conductivity information.
2Ease of operation
If borehole effects are not compensated for, then the measurement process remains simple, but it becomes hard to use or interpret the measurements to infer formation properties
Solution Approach 1:
The method performs preliminary computation of a borehole-inclusive modeled tensor using known borehole parameters before analyzing formation properties. By pre-calculating and removing the borehole effects in advance, the method simplifies the subsequent interpretation process, allowing direct extraction of formation properties from the corrected measurements without complex post-processing.
Solution Approach 2:
The optimization process uses feedback by comparing the borehole-corrected measured conductivity tensor with a formation-only modeled tensor. The method iteratively adjusts formation property parameters to minimize the difference between these tensors, providing feedback-driven refinement that enhances interpretation accuracy while maintaining operational efficiency.
3Measurement precision
If a borehole-inclusive modeled tensor is computed and optimization is performed, then accurate formation properties can be determined, but the computational complexity and processing time increase
Solution Approach 1:
The method applies partial action by selecting a subset of borehole parameters for inclusion in the borehole-inclusive modeled tensor based on their relative impact on measurement accuracy. By focusing computational resources on the most significant parameters (such as mud conductivity and hole diameter) rather than all possible parameters, the method achieves high accuracy while limiting computational complexity.
Solution Approach 2:
The optimization process efficiently handles parameter changes by using the borehole-inclusive modeled tensor to isolate formation property parameters from borehole parameters. This parameter separation allows the optimization to focus only on formation properties (conductivity, dip angle, azimuth) without being confounded by borehole parameter variations, reducing the dimensional complexity of the optimization problem.
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 method effectively reduces the impact of borehole and tool effects, allowing for the accurate estimation of formation properties such as horizontal and vertical conductivities, dip angle, and azimuth, enhancing the robustness and efficiency of resistivity measurements.
Implementation Method 1
Conventional induction tools, for example, work by using a transmitting coil (transmitter) to set up an alternating magnetic field in the earth formations. This alternating magnetic field induces eddy currents in the formations.
Implementation Method 2
One or more receiving coils (receivers), disposed at a distance from the transmitter, detect the current flowing in the earth formation. The magnitudes of the received signals are proportional to the formation conductivity.
Data Source
AI summary
A method for correcting formation properties due to effects of a borehole is disclosed. The method includes obtaining voltage measurements using a logging tool disposed in a borehole penetrating a subsurface formation. The method further includes using a processor to: determine a tensor for the formation using the voltage measurement. For a given set of parameters, the processor determines, based upon the voltage measurements, a parameter value for each parameter in a subset of the set of parameters. The method further uses the processor to compute a borehole-inclusive modeled tensor that includes the effects of the borehole using the parameter values, optimize the parameter values using the determined tensor and the borehole-inclusive tensor, compute an optimized tensor using the optimized parameter values, compute a borehole corrected tensor using the optimized tensor, and determine at least one borehole corrected formation property using at least one of the borehole corrected tensor or the optimized parameter values.