Abstract
Detecting the onset and production of sand and solids from a well is considered of critical value for the safe and economically effective operation of any oil and gas field. Produced sand may cause disruption in the production and/or damage to equipment with severe negative consequences. A key element of production optimization is the ability to determine the maximum sand-free production rate with a high degree of confidence. The reliability of acoustic sand detectors is normally sensitive to various factors, including blind spots due to acoustic interference from, for example, nearby valve actuation, remotely operated vehicle activities, and low-velocity/transient flow regimes. Using a multiphase flowmeter to detect and measure sand and solids in the production stream has been studied for over 10 years. Our study advances the application of multiphase flowmeters to sand detection by adding cloud-based monitoring and quantification algorithms.
Examination of the radioactive source, which is the core of multiphase flowmeter technology, demonstrated that it is difficult to distinguish between sand and water at the expected range of process conditions with a reasonable confidence level in real time. To obtain sand measurements using a multiphase flowmeter, the water content of the fluid must be known and further processing steps developed to reprocess the data and identify sand.
A cloud-based digital condition monitoring system enables real-time collection, storage, and processing of the data obtained from the field, which unlocks additional features that are not possible with a real-time in situ computer. Algorithms for evaluating and differentiating the effect of sand presence and water content fluctuations were developed and tested. Quantification algorithms were created and verified during flow loop testing.
The solution is currently implemented on multiple subsea projects where multiphase flowmeter units have been installed. The multiphase flowmeters are now being used to detect and measure the production of sand and solids in subsea oil and gas wells. Accuracy of the solution is demonstrated by comparing acoustic sand detection sand volumes received at the surface with the output from the cloud sand detection algorithms.
Use of multiphase flowmeter data with a cloud-based monitoring system for sand detection is a reliable solution that reuses available infrastructure without retrofitting additional equipment. This is a critical development in digital technology demonstrating how smart oil fields are becoming a reality and being used today.
