Session: 11-10-01 Digitalization of Subsurface Wells Systems, Subsea Systems and Operations

Paper Number: 127882

127882 - Investigation of Multiphase Flow Leak Detection in Pipeline Using Time Series Analysis Technique 

Objectives:

Detecting chronic small leak sizes can be challenging because they may not produce significant or easily noticeable changes in flow rates or pressure differentials. Therefore, specialized techniques are often required to identify and locate chronic small leaks accurately in pipeline systems. The current study aims to address this gap by developing a method to detect and locate multiphase flow leaks in pipelines using time series analysis techniques.

Methodology, procedure, and process:

An experimental flow loop apparatus, featuring a 2-inch (0.0508 m) diameter and extending 22.6 feet (6.9 m) in length, has been employed to carry out our experiments. The experiments encompass a range of liquid flow rates varying between 170 and 350 kg/min and gas flow rates ranging from 10 to 60 g/min. The system was equipped with three distinct leak sizes, measuring 1.8 mm, 2.5 mm, and 3 mm, each separated by 90 mm. Data collected from four dynamic pressure sensors and a hydrophone was subjected to various time series analysis including Wavelet transforms and Fast Fourier Transforms (FFTs) to detect and pinpoint the location of pipeline leaks.

Results, observation, and conclusion:

The obtained results indicate that dynamic pressure sensors are effective in detecting leak scenarios, as well as distinguishing between single and multiple leaks. However, for chronic small leaks, analyzing the standalone pressure response over time is generally not sufficient for detection. Time series analysis techniques play a crucial role in accurately identifying chronic small-sized pipeline leaks. Additionally, the Fast Fourier Transform (FFT) of hydrophone data is a valuable tool for leak identification under various flow regimes and demonstrates greater accuracy as compared to dynamic pressure signals. Furthermore, it is noted that detecting leaks in slug flow is more straightforward than in dispersed bubble flow within the pipeline due to smaller gas pockets and lower leak flow.

Novel/Additive information of the study:

This study introduces the application of time series analysis on dynamic pressure and hydrophone signals to detect chronic small-sized leaks in multiphase flow pipelines. It also delves into the impact of leak sizes and flow regimes, providing valuable insights into assessing leak scenarios and addressing crucial safety, environmental, and economic concerns.

Presenting Author: Abinash Barooah Texas A&M

Presenting Author Biography: Dr. Abinash Barooah is working as Post Doctoral Research Associate in the Petroleum Department of Texas A&M University at College Station. His main research interest are in multiphase flow, flow assurance, leak detection, data analysis, Statistical analysis, Machine learning.

Authors:

Abinash Barooah Texas A&M
Muhammad Saad Khan Texas A&M University at Qatar
Hicham Ferroudji Texas A&M University at Qatar
Mohammad Azizur Rahman Texas A&M University
Rashid Hassan Texas A&M University
Ibrahim Hassan Texas A&M University at Qatar
Ahmad K. Sleiti Qatar University
Sina Rezaei Gomari Teesside University
Matthew Hamilton Memorial University of Newfoundland