Automated Gas Deliverability Test Selection System
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Solution Overview
Problem
Current deliverability tests for gas wells often result in incorrect assessments, leading to delays and increased costs due to inadequate planning and budgeting, as the selection of the appropriate test type is not accurately foreseen based on well attributes.
Innovation Solution
An automated method for selecting and prioritizing gas deliverability tests based on well performance, sustainability, geochemical analysis, and pressure build-up data, using a decision tree approach to determine the most suitable test type, such as with or without a separator, to optimize resource allocation and reduce unnecessary testing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If deliverability tests are performed without accurate planning based on well attributes, then testing can be conducted, but delays and increased costs occur due to incorrect test selection
Solution Approach 1:
The system performs preliminary analysis of well attributes (production history, sustainability metrics, geochemical data, pressure build-up) before selecting the deliverability test type. This advance planning ensures the correct test is chosen from the outset, preventing delays caused by incorrect test selection and redos.
Solution Approach 2:
The system uses feedback from multiple data sources including production sustainability assessments, geochemical water analysis, shut-in bottom hole pressure measurements, and pressure build-up data to continuously refine test selection decisions, improving accuracy over time.
2Reliability
If deliverability tests are performed without accurate planning based on well attributes, then testing can be conducted, but unnecessary costs increase due to incorrect test selection
Solution Approach 1:
The system performs preliminary analysis of well attributes (production history, sustainability metrics, geochemical data, pressure build-up) before selecting the deliverability test type. This advance planning ensures the correct test is chosen from the outset, preventing delays caused by incorrect test selection and redos.
Solution Approach 2:
The system uses feedback from multiple data sources including production sustainability assessments, geochemical water analysis, shut-in bottom hole pressure measurements, and pressure build-up data to continuously refine test selection decisions, improving accuracy over time.
3Adaptability or versatility
If deliverability tests are planned without foreseeability based on well attributes, then testing can proceed, but planning and budgeting accuracy deteriorates
Solution Approach 1:
The system performs preliminary analysis of well attributes (production history, sustainability metrics, geochemical data, pressure build-up) before selecting the deliverability test type. This advance planning ensures the correct test is chosen from the outset, preventing delays caused by incorrect test selection and redos.
Data Source
AI summary
Systems and methods for selecting and performing gas deliverability tests are disclosed. In one embodiment, a method of performing a gas deliverability test includes drilling a well, operating the well to produce gas, determining a sustainability of the well, and determining at least one of a shut-in bottom hole pressure and pressure build-up of the well and a geochemical analysis of the well. The method further includes selecting a deliverability test based at least in part on a duration of an operation of the well, a sustainability of the well, and at least one of the shut-in bottom hole pressure, the pressure build-up and the geochemical analysis of liquids of the well. The method also includes applying the deliverability test to the well.


