Real-Time Signal Strength Determination in Well-Test Data
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Solution Overview
Problem
Existing well test data analysis methods struggle to accurately determine signal strength, leading to distorted pressure derivative profiles and misinterpretation of reservoir characteristics due to low signal-to-noise ratios.
Innovation Solution
A computer-implemented method that involves performing a well test, receiving raw pressure data from a downhole gauge, determining the amplitude of noise, computing the signal-to-noise ratio, and comparing it against a threshold. Based on the SNR, a simulation of the well is constructed, and corrective actions are taken to improve data quality if the SNR is below the threshold.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If well test data is collected without signal strength evaluation, then the testing process is simple and fast, but the accuracy of reservoir parameter determination deteriorates due to distorted pressure derivative profiles
Solution Approach 1:
The patent applies preliminary action by evaluating signal strength and determining whether corrective actions are needed before proceeding with reservoir parameter determination. The system calculates signal-to-noise ratio and compares it against threshold values in advance, allowing the analysis to proceed only when data quality is sufficient, thus preventing distorted results while maintaining efficient workflow.
Solution Approach 2:
The patent implements feedback by continuously monitoring signal strength during the well test and providing real-time guidance on whether corrective actions are required. The system compares calculated signal-to-noise ratios against predetermined thresholds and feeds back information about data quality status, enabling dynamic adjustment of the testing process to ensure accurate reservoir parameter determination.
2Measurement precision
If corrective actions are taken to improve signal strength, then the accuracy of pressure derivative profiles improves, but the testing time and operational complexity increase
Solution Approach 1:
The system provides real-time feedback on signal strength during the well test, allowing operators to understand when corrective actions are needed and for how long. By monitoring signal-to-noise ratios continuously and comparing against thresholds, the system enables timely interventions to restore signal strength without unnecessarily extending the entire test duration, thus balancing accuracy requirements with time efficiency.
3Reliability
If signal strength is not maintained above threshold, then the testing operation is simpler and faster, but the reliability of production rate forecasting deteriorates
Solution Approach 1:
The patent applies preliminary action by assessing signal strength before finalizing the well test results. The system calculates signal-to-noise ratios and determines in advance whether the data quality is sufficient for reliable production rate forecasting. This preliminary evaluation ensures that only high-quality data is used for forecasting, maintaining reliability while avoiding unnecessary corrective actions that would complicate operations.
Data Source
AI summary
System and methods include performing a well test on a well, the well comprising a subterranean wellbore with a tubular. The computer system can receive raw data from a pressure gauge residing within the tubular, the raw data comprising discrete pressure values in a time series for a fluid flowing through the tubular. From the raw data, the computer system can determine an amplitude of noise for each pressure value in a time series and derive signal-to-noise ratio (SNR) for each pressure value in a time series based on the determined amplitude. The SNR can be compared against a predetermined threshold value. When SNR is above the threshold, a simulation of the well can be constructed to forecast well production rates. If SNR is below the threshold, corrective action can be taken to improve SNR of pressure values read from a sensor in the well.