Novel Data-Driven Methodology for Production Allocation Calculation Utilizing Physics-Based Models Coupled and Integrated Within a Digital Framework

Determining the production from each well is crucial for financial and technical purposes. Moreover, this production can be anticipated using several different techniques. This paper describes the procedures to calculate the production allocated to each well in a giant gas-producing field by utilizing physics-based models that are orchestrated in a dynamic digital platform to provide a robust and efficient solution. The cases for this study of allocating gas rates to individual wells were performed using a digital platform as the primary tool utilized to account for the main productional location factors such as well tests and events that are used to estimate actual production volumes. Subsequently, relevant data is extracted, filtered, and loaded into the system in a dynamic interaction with fewer human interventions. The methodology for calculating the production allocated followed these main steps: a) Determine production per well under existing possible measures, b) Determine well contribution factors, c) Distribute actual rates and production according to allocation factors. By using polynomial equations where the inflow performance of the gas wells was verified, the allocation rates were calculated at every desired point of the network. Having an integrated platform proved to be advantageous since it provided a seamless link between different relevant manual and real-time databases and well / network models bringing unique capabilities and benefits. While comparing this integrated and holistic approach versus the previously established one, it was highlighted that production allocation using mainly choke sizes and well test as a sole source for well production can bring significant variations. This creates production mismatches at the well level; therefore, it portrays a misrepresentation of the actual field conditions. Numerous challenges, which are usually faced while calculating the production allocation process, were overcome during the development of this study, such as frequent surface network changes, lack of databases communication, and daily variations on the on/off wells’ status. Furthermore, the data management capabilities of the framework allowed data to be quickly accessible by the users whenever needed allowing them to visualize across the different teams and departments, taking actions when and where required. This standardized methodology provided consistency, reliability, and accuracy, which can be replicated on oil-producing fields and networks; it can be enhanced and scaled in order to incorporate other business processes such as well allowable calculation and voidage monitoring.