Pixelated Formation Model for Ultra-Deep Resistivity Logging
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Solution Overview
Problem
Deep resistivity logging tools face challenges in interpreting formation data due to the complexity of ultra-deep detection ranges, which results in multiple layers and the failure of qualitative methods to accurately identify formation zones suitable for producing hydrocarbons.
Innovation Solution
The implementation of a pixelation method and distance-to-bed-boundary (DTBB) inversion algorithm, combined with a processor-based system to generate a formation model by converting multiple DTBB solutions into pixelated solutions and calculating a model average, allows for efficient analysis and identification of formation boundaries and uncertainties.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Length of stationary object
If ultra-deep detection range is used to detect formation boundaries 100 feet radially outward, then detection range is improved, but formation data complexity increases making qualitative methods fail
Solution Approach 1:
The patent segments the continuous formation data into discrete depth intervals (e.g., 1-foot intervals) and assigns pixel values to represent formation characteristics at each interval. This segmentation transforms the complex continuous data into manageable discrete units that can be systematically analyzed and visualized, resolving the complexity issue while preserving the ultra-deep detection capability.
2Measurement precision
If multiple inversion solutions are generated to evaluate formation zones, then measurement precision is improved, but device complexity and processing difficulty increase
Solution Approach 1:
The patent merges multiple DTBB inversion solutions by converting them into pixelated form and calculating a model average (mean pixel values). This combining approach synthesizes information from multiple solutions into a single integrated formation model, maintaining measurement precision while reducing processing complexity through systematic averaging.
Solution Approach 2:
The patent creates simplified pixelated representations (copies) of the complex inversion solutions. Each pixel serves as a condensed representation of formation characteristics at a specific depth interval, allowing efficient storage, visualization, and analysis without processing the full complexity of the original inversion data.
3Ease of operation
If qualitative methods such as correlation are used to interpret tool responses, then ease of operation is maintained, but reliability of formation zone identification deteriorates
Solution Approach 1:
The patent transforms the interpretation approach by changing from qualitative correlation methods to a quantitative pixel-based model averaging approach. By converting formation data into numerical pixel values and computing statistical averages, the method maintains operational simplicity while significantly improving the reliability of formation zone identification through more robust quantitative analysis.
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 condenses hundreds of inversion solutions into a single formation model, enabling accurate evaluation of subterranean formations and steering of drill bits to target hydrocarbon-producing layers, thereby improving the precision of wellbore trajectory planning.
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
Implementation Method 2
When operated at low frequencies, the resistivity tool may be called an induction tool, and at high frequencies the resistivity tool may be called an electromagnetic wave propagation tool
Implementation Method 3
at high frequencies the resistivity tool may be called an electromagnetic wave propagation tool
Data Source
AI summary
A system and method for evaluating a subterranean earth formation as well as a method of steering a drill bit in a subterranean earth formation. The system comprises a logging tool that is operable to measure formation data and locatable in a wellbore intersecting the subterranean earth formation. The system also comprises a processor that is in communication with the logging tool. The processor is operable to calculate multiple distance-to-bed-boundary (DTBB) solutions using the measured formation data, identify DTBB solutions that satisfy a threshold, convert the identified solutions into pixelated solutions by dividing the identified solutions into pixels, generate a formation model based on the pixelated solutions, and evaluate the formation using the generated formation model.