Adaptive Logging Workflow for Bandwidth-Limited Drilling
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Solution Overview
Problem
Current oil field drilling operations face challenges in making proactive decisions due to limited communication bandwidth, measurement accuracy, and data interpretation limitations during logging-while-drilling (LWD) or wireline logging operations, as the actual properties of geological formations are typically unknown until after drilling begins.
Innovation Solution
The implementation of an adaptive learning engine-based workflow management system that adjusts logging operations in real-time or near-real-time using collected measurements, operator inputs, and automation rules, allowing for adjustments in parameters such as movement rate, signal power, frequency, and antenna orientation to optimize data collection and processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If real-time logging operations are performed during drilling, then productivity is improved, but communication bandwidth limitations prevent effective data transmission
Solution Approach 1:
The system performs preliminary processing of logging data downhole before transmission to the surface. The logging while drilling tool processes and filters data locally, preparing only essential information for transmission through the limited bandwidth communication channel, thereby maintaining productivity while overcoming communication limitations.
Solution Approach 2:
The invention extracts and separates critical logging parameters from the complete data set for prioritized transmission. By identifying and transmitting only the most important formation property data, the system overcomes bandwidth constraints while preserving essential information for drilling decisions.
2Measurement precision
If measurement accuracy is increased through more precise logging tools, then data quality is improved, but device complexity and cost increase
Solution Approach 1:
The system applies different processing quality levels to different logging parameters based on their importance and uncertainty. Critical parameters receive enhanced processing and quality control, while less critical parameters use standard processing, thereby achieving high measurement precision where needed without uniformly increasing device complexity throughout the entire logging tool.
3Quantity of substance
If more logging parameters are collected simultaneously, then data completeness is improved, but data processing limitations reduce effective analysis capability
Solution Approach 1:
The logging tool segments and categorizes multiple measurement parameters into distinct groups (e.g., formation properties, tool status, environmental parameters). This segmentation enables systematic processing and prioritization, allowing the system to handle a comprehensive set of parameters while managing processing complexity through structured organization and selective deep analysis of critical parameters.
Data Source
AI summary
In an embodiment a method of automatic adjustment of logging, processing, inversion, and visualization operations is disclosed. The method comprises gathering data about formation properties in a database, filtering the gathered data, generating rules based on the filtered data, and providing automatic adjustments to automatically adjust the logging, processing, inversion, and visualization operations. The gathered data includes a plurality of in-well measurement points and a plurality of wells in a given geological area. A quality factor is derived based on a difference between the automatic adjustments and parameters that an operator communicates as a best parameter. The quality factor is used to determine which of the gathered data is to be stored in the database. The rules are applied to a next iteration of data that is to be gathered. The method repeats until no further improvement is obtained.