Distributed Acoustic Sand Inflow Detection
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Solution Overview
Problem
Current methods for detecting sand inflow in wellbores are limited by their inability to provide real-time, quantitative measurements of sand ingress, leading to reduced oil production and deferred operations due to false positives and the inability to accurately locate and quantify sand production.
Innovation Solution
A system utilizing distributed acoustic sensors and real-time signal processing to extract frequency domain features from acoustic signals, allowing for the detection of sand inflow by comparing spectral centroids and spreads to thresholds, and providing a quantitative measurement of sand ingress through spectral analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If acoustic point sensors are used to detect sand particles, then sand presence can be detected, but the detection is limited to surface equipment and is qualitative only
Solution Approach 1:
The patent divides the wellbore into multiple monitoring zones by placing multiple acoustic sensors at different depths along the production string. Each sensor monitors a specific zone, enabling both detection of sand presence and identification of the specific depth zone where sand is entering the wellbore, thus resolving the contradiction between detection capability and location information.
2Reliability
If production is choked back to reduce sand production, then sand production is reduced to acceptable levels, but oil production is reduced by over 75%
Solution Approach 1:
The patent implements a feedback system where acoustic sensors continuously monitor sand production in real-time, and this information is used to dynamically adjust production parameters. Instead of permanently choking back production, the system provides feedback about actual sand ingress locations and rates, enabling operators to make informed decisions about when and where to apply sand control measures, thereby maintaining higher overall production while controlling sand issues.
3Measurement precision
If distributed acoustic sensors with real-time signal processing are used, then real-time sand inflow detection and quantification is enabled, but device complexity increases
Solution Approach 1:
The patent extracts and analyzes only the relevant frequency components of the acoustic signals generated by sand particles. By focusing on specific frequency ranges characteristic of sand ingress and using spectral analysis to isolate these signals from background noise, the system achieves quantitative sand detection without requiring overly complex processing of the entire acoustic spectrum, thus managing device complexity while maintaining measurement precision.
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 real-time detection and quantification of sand inflow, reducing operational risks and improving production efficiency by accurately identifying sand ingress zones and facilitating targeted remediation.
Implementation Method 1
Such contact creates stress waves that are captured as sound signals by the acoustic sensors mounted on the pipe wall
Data Source
Figure 1
Figure 2
Figure 3A~3B
AI summary
A method of identifying and detecting sand inflow into a wellbore is provided. The method comprises: obtaining a sample data set, wherein the sample data set is a sample of an acoustic signal originating within a wellbore (114) comprising a fluid; detecting a broadband signal within the sample data set, wherein the broadband signal at least includes a portion of the sample data set at frequencies above 0.5 kHz, determining spectral features of the broadband signal, wherein the spectral features are indicative of the acoustic signal across a frequency spectrum; comparing the spectral features of the broadband signal with a signal reference, wherein the signal reference comprises thresholds or ranges for a plurality of frequency domain features; determining that the spectral features of the broadband signal meet or exceed the signal reference; and determining the presence of sand inflow into the wellbore (114) based on determining that the spectral features of the broadband signal meet or exceed the signal reference.