Deep Transient Testing Gas Rate Integration Workflow
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Solution Overview
Problem
Current formation testing technologies face challenges in accurately quantifying and monitoring hydrocarbon volumes and surface gas emissions during deep transient testing operations, leading to inefficiencies and potential environmental impacts, such as CO2 and greenhouse gas emissions, which are not effectively managed due to limitations in measuring and integrating downhole and surface data in real-time.
Innovation Solution
A method that involves a downhole well tool and control system to measure fluid properties and predict surface gas rates by integrating downhole and surface data, enabling real-time monitoring and control of gas emissions, and refining gas rate calculations through workflows that determine mass and volume rates of gases pumped from the formation, using sensors and neural network models for accurate gas composition analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If downhole and surface data are integrated in real-time, then measurement precision of gas rates is improved, but device complexity increases
Solution Approach 1:
The system divides the measurement and integration process into distinct modular components: downhole measurement tools, surface measurement equipment, data transmission systems, and integration software. Each module performs a specific function, making the overall complex system manageable and maintainable while achieving high measurement precision through coordinated operation of all segments
Solution Approach 2:
The integrated platform is designed to perform multiple functions within a unified system: it measures downhole parameters, transmits data in real-time, processes surface measurements, integrates datasets, and generates comprehensive analytics. This multi-functionality reduces the need for separate dedicated systems while maintaining measurement precision across all parameters
2Object-affected harmful factors
If real-time monitoring and control of gas emissions is implemented, then environmental impact is reduced, but use of energy increases
Solution Approach 1:
The system implements continuous real-time feedback loops where downhole and surface gas rate measurements are constantly monitored, compared against emission thresholds, and used to automatically adjust operational parameters. This feedback mechanism enables proactive emission reduction by triggering alerts or automatic control actions before harmful emission levels are reached, minimizing environmental impact while optimizing energy use through intelligent control rather than continuous high-energy operation
Solution Approach 2:
The system dynamically adjusts operational parameters such as flow rates, pressure settings, and circulation rates based on real-time gas rate measurements and emission monitoring. By changing these parameters optimally in response to measured conditions, the system minimizes harmful emissions while avoiding unnecessary energy consumption associated with fixed high-level operation
3Measurement precision
If accurate gas composition analysis is performed using sensors and neural network models, then measurement precision is improved, but loss of time in processing increases
Solution Approach 1:
The system performs preliminary processing of sensor data including filtering, normalization, and feature extraction before data leaves the measurement devices. Neural network models are pre-trained offline with extensive datasets, so during real-time operation they require minimal processing time. This preliminary preparation enables rapid accurate gas composition analysis without significant time loss during actual measurement and monitoring operations
Data Source
AI summary
Systems and methods presented herein generally relate to a formation testing platform for quantifying and monitoring deep transient testing (DTT) surface gas rates formation testing data collected by a downhole well tool, which may be adjusted based on surface gas rates directly measured by surface equipment. For example, a method includes flowing one or more fluids from a subterranean formation to flow through a downhole well tool disposed in a wellbore of a well during a deep transient testing (DTT) operation performed by the downhole well tool. The method also includes measuring data related to one or more properties of the one or more fluids using one or more downhole fluid analysis sensors disposed within the downhole well tool, and predicting, via a control system, a first predicted DTT surface gas rate based on the data measured related to the one or more properties of the one or more fluids.