The Third Generation Leak Detection and Repair (LDAR3) System

In the U.S., 55% of all air emissions from refineries and 22% of emissions from non-refineries are due to fugitive volatile organic compound (VOC) emissions from leaking equipment components such as valves, flanges, compressors, connectors, etc.  Leak Detection and Repair (LDAR) is therefore an important component of environmental operations at these facilities to control fugitive VOC emissions.

As shown in Figure A, Traditional LDAR, the current work practice (CWP) for LDAR, involves manual detection of leaks using EPA Method 21 monitors.  The operators use the handheld monitors to “sniff” individual components for leak detection.  A large portion of the industrial facilities where LDAR is critical for environmental protection have hundreds of thousands of such components, making the CWP extremely expensive, up to $1 million per facility per year.   

Recently, the EPA proposed an alternative work practice (AWP), also referred to as Smart LDAR, to address the inefficiencies and challenges associated with the CWP.  As shown in Figure B, Smart LDAR involves the use of infrared (IR) cameras that detect VOC plumes from components that need repair.  The IR cameras more than quadruple the number of components that an operator can monitor per hour.  However, Smart LDAR is still a manual process, susceptible to operator error, can have delayed leak identification, and does not provide real-time leak notifications for immediate repair.  Thus, Smart LDAR leaves significant room for improvement.

Providence has developed an innovative LDAR concept referred to as LDAR3.  LDAR3 is a patent-pending system.  Smart LDAR changes the monitoring tool from Method 21 monitors to IR cameras, whereas LDAR3 automates the leak detection process.  Automation is made possible by newly developed algorithms that automatically process IR images and recognize VOC plumes as leaks (see LDAR3 process in Figure C).  Automation is a powerful enabler.  Firstly, because the leak detection process is automated, it allows leak check frequency to increase from bi-monthly to weekly or daily, thereby reducing emissions from leaks that would be undetected for longer periods under traditional or Smart LDAR.  Secondly, because of the increased monitoring frequency, the requirement for IR cameras’ detection limit can be relaxed per EPA Alternative Work Practice (AWP) protocol using Monte Carlo simulation procedures.  Thirdly, the automation allows an IR camera to cover a large process area and significantly reduces the labor cost associated with leak detection.