公开(公告)号：US20220307357A1

公开(公告)日：2022-09-29

申请号：US17293454

申请日：2020-06-12

Applicant: LANDMARK GRAPHICS CORPORATION

Inventor： Ajay Pratap Singh ,  Suryansh Purwar ,  Ashwani Dev ,  Satyam Priyadarshy

IPC: E21B43/16 ,  E21B47/06 ,  E21B47/003

Abstract: System and methods for tuning equation of state (EOS) characterizations are presented. Pressure-volume-temperature (PVT) data is obtained for downhole fluids within a reservoir formation. A component grouping for an EOS model of the downhole fluids is determined, based on the obtained PVT data. The component grouping is used to estimate properties of the downhole fluids for a current stage of a downhole operation within the formation. A machine learning model is trained to minimize an error between the estimated properties and actual fluid properties measured during the current stage of the operation, where the component grouping for the EOS model is iteratively adjusted by the machine learning model until the error is minimized. The EOS model is tuned using the adjusted component grouping. Fluid properties are estimated for one or more subsequent stages of the downhole operation to be performed along the wellbore, based on the tuned EOS model.