Azimuthal Resistivity Ranging for Multi-Well Detection While Drilling
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Solution Overview
Problem
Existing methods struggle to accurately detect and locate multiple target wells extending through a subterranean formation surrounding a new well being drilled, particularly when they are spatially aligned in various angles or come close to the new well simultaneously or sequentially, and there is uncertainty about the number of target wells.
Innovation Solution
Employing ultradeep azimuthal resistivity (UDAR) measurements with a downhole tool to acquire azimuthal resistivity data, which is processed using pixel-based, model-based, or machine-learning inversion processes to detect and locate multiple target wells, incorporating geosteering operations for dynamic drilling adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional transverse antenna measurements are used for casing and pipe detection, then single target well detection is achieved, but multiple target wells cannot be simultaneously detected
Solution Approach 1:
The patent transitions from conventional transverse antenna measurements to ultradeep azimuthal resistivity measurements, adding the azimuthal dimension to the detection capability. This dimensional change enables the system to distinguish between multiple target wells by measuring resistivity variations from different azimuthal directions, thereby simultaneously detecting multiple targets that would be indistinguishable using conventional single-dimension methods.
Solution Approach 2:
The patent changes the measurement parameters by using ultradeep azimuthal resistivity measurements instead of conventional transverse antenna measurements. This parameter change involves measuring resistivity at multiple azimuthal angles and at ultradeep depths, which provides additional information dimensions that enable differentiation and simultaneous detection of multiple target wells with varying spatial configurations.
2Reliability
If imaging-based approaches are used for well detection, then detection in high inclination or perpendicular cases is improved, but detection of multiple wells at various angles is limited
Solution Approach 1:
The patent implements a universal detection system using ultradeep azimuthal resistivity measurements that can handle multiple spatial configurations simultaneously. The system is designed to detect target wells in various orientations (parallel, perpendicular, arbitrary angles) and spatial arrangements (simultaneous or sequential close approaches) using the same measurement and processing methodology, eliminating the need for different specialized approaches for different scenarios.
Solution Approach 2:
The patent employs dynamic inversion processing that can adapt to different spatial configurations of target wells. The inversion algorithm dynamically adjusts to detect wells regardless of their orientation or relative positions, providing a flexible solution that maintains reliability across varying geological and operational conditions without requiring predetermined knowledge of well configurations.
3Device complexity
If processing is configured for known number of target wells, then model-based inversion is simplified, but inability to handle unknown number of target wells limits applicability
Solution Approach 1:
The patent implements a dynamic processing system that can adapt its complexity based on the detection needs. The system can operate in different modes: when the number of target wells is known, it uses streamlined model-based inversion; when the number is unknown, it employs pixel-based inversion or machine learning approaches that automatically determine the number of targets. This dynamic adaptability allows the system to maintain reasonable complexity while handling all scenarios.
Solution Approach 2:
The patent changes the processing parameters and methodologies based on the available information. When the number of target wells is unknown, the system switches to parameter-free or data-driven approaches (pixel-based inversion, machine learning) that can infer the number of targets from the measurement data itself, rather than requiring predetermined knowledge of target quantities.
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 precise detection and localization of multiple target wells, facilitating effective geosteering to navigate the new well's path, avoiding existing wells and forming designed patterns, even when the number of target wells is unknown.
Implementation Method 1
azimuthal resistivity measurements are acquired by a downhole tool
Implementation Method 2
The processing can involve an inversion process that generates synthesized tool response data from a formation model
Data Source
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AI summary
Methods are provided that detect and locate multiple target wells that extend through a subterranean formation in a region surrounding a new well being drilled. The methods deploy a downhole tool in the new well while drilling the new well and configuring the downhole tool to acquire ultradeep azimuthal resistivity measurements while drilling the new well. The ultradeep azimuthal resistivity measurements are processed to detect and locate multiple target wells that extend through the subterranean formation in the region surrounding the new well.