- Limit harmful flaring by reducing the frequency of planned and unplanned shut-downs
- Gain accurate well-by-well flow rate intelligence to optimize production and volumes
- Remove the unnecessary complexity of manual well analysis and workflows
Flaring and venting in oil and gas operations is a major environmental concern, and the source of harmful gases, including methane and CO2. According to estimates from the World Bank, 140 billion cubic meters of natural gas were flared in 2019, resulting in 300 million tons of CO2 emitted into the atmosphere. Most governments have taken measurements to reduce flaring to the best possible minimum, with only intermittent flaring to be conducted. Emission documentation required by operators assure a responsible conduct within those national regulations set. However, the cause for most intermittent flaring lies in excess gas needing to be flared in order to assure HSE regulations are adhered to. With that, flaring is a challenge hard to be avoided in most circumstances. For example, a processing facility can only consume produced gas as fuel, and any additional gas must be either exported, reinjected or flared. In case of operational upsets, additional flaring may be required for safety reasons. By understanding flow rates and reducing flow instabilities, the shut-down frequency in operations can be reduced, resulting in less emissions.
Our self-calibrating, real-time solutions for flow insights allow to both mimic multiphase flow and assess the risks of flow instabilities in wells and pipelines. This insight helps the operator optimize flow rates and reduce the number of process shutdowns due to overfilling the inlet separator with liquids. Smarter operations consequently reduce the need of flaring and venting.
Our solutions are based on a hybrid technology, combining the predictive capabilities of physical models with the self-adjusting capabilities of machine learning over time. First, the physical models in our transient multiphase flow simulator (FLUX Simulator) are calibrated based on available reference and historical test data, for example fluid data, temperature and pressure, in the well, on the surface or on the topsides. The available, historical well test data is utilized to develop an automated model that self-adjusts over time. New well test data is routinely captured in the system in real-time to update the model.
The Value Gain
With this, we can predict flow rates and instabilities of the individual wells and pipelines, enabling the operator to make better operational decisions, such as adjusting the choke position, reducing the separator pressure or adjusting the lift gas rate. In a scenario where an operator produces from 20 wells, where shut-downs per well over a total of one day per year can be avoided, the operator creates an additional 20 days of well productivity per annum that otherwise would have been lost. This improves production volumes over time and reduces operational costs related to shut-down periods. Importantly, optimizing flow stability improves energy efficiencies and related emission intensity. A 10% increase in production efficiency delivers a 4% reduction in emission intensity.*
Our system considers many more inputs than what one would typically find in a curve-fit type of analysis within a spreadsheet. We can therefore aim to predict the individual wells’ flow rates and flow instabilities more accurately than through the traditional spreadsheet-based system, in addition to reducing the complexity of accessing and analyzing the data for the end user. Our online system can be accessed through the operator’s system or through our own user interface, FLUX Applied (beta).
*McKinsey Report: Toward a net-zero future
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