Abstract
For most of the life of Tengiz oil field, production has been constrained by the processing capacity of the existing plant facilities, therefore, the excess capacity of oil production above facility capacities (so called whitespace) has been used to compensate losses while conducting maintenance, reservoir surveillance and other field activities without impact on overall production. This paper describes an improved production forecasting approach to optimize field activities planning.
The initial forecasting methodology required manual inputs. These manual set-up of models for predicting future production is time consuming and can sometimes be subject to human errors. Therefore, it was decided to automate the process and move from an Excel-based tool to digital solutions.
The WhiteSpace Dashboard is a web-based tool designed to optimize and automate inputs for Integrated Production Modelling (IPM) and improve the decision-making process, while maximizing production deliverability to the plants. The tool embodies a set of automated workflows that increase the accuracy of production modeling based on automated data inputs, additional functionalities, data quality checks, ability to run several simulation cases on a cloud server and ability to compare the results. The new dashboard also aids to minimize human error and allows QA/QC of input and output data and parameters.
The development of a fit-for-purpose digital tool, the WhiteSpace Dashboard, allowed TCO to combine all existing systems of record into one database with the opportunity to integrate various activities into one set of data input for production forecasting.
All the subsurface data required for production forecasting is also automatically pulled from the Digital Oil Field system of record with functionality to change the values for subsurface data such as Gas-Oil-Ratio (GOR), reservoir pressure and productivity index inside the web interface. Users have the flexibility to set up several simulation cases, run them in queues, view the status of the runs, and analyze the simulation results any time after completion.
The output of the production modeling is the production forecast, and users have all the required functionalities to analyze each scenario in details. Additionally, users can compare several cases on a single chart. The developed tool significantly improves selection of the best schedule for operational activities to minimize risks of production losses, optimize production and meet production targets.
This paper aims to provide an overview of the integrated production forecasting tool and to share the best practices in the planning of operational activities in the field with optimized schedule and minimized impact on overall field production.
