Using Data Analytics and Manage by Exception Methodology to Analyze, Confirm and Predict Well Behavior Using Integrated Modeling Approach


Authors

Rachelle Christine Cornwall (ADNOC Onshore) | Saber Mubarak Al Nuimi Nuimi (ADNOC Onshore) | Deepak Tripathi Tripathi (Weatherford) | Melvin Hidalgo Hidalgo (Weatherford) | Sandeep Soni Soni (Weatherford) | Jose Isambertt Isambertt (Weatherford)

Publisher

IPTC - International Petroleum Technology Conference

Publication Date

January 13, 2020

Source

International Petroleum Technology Conference, 13-15 January, Dhahran, Kingdom of Saudi Arabia

Paper ID

IPTC-19980-Abstract


Abstract

A workflow-based approach was implemented to improve the efficiency of Integrated Asset Operations Model (IAOM) processes and to enhance the reliability of production profiles. This approach is based on automated validation, data analytics, and management-by-exception rules to improve the work process efficiency and to reduce manual interventions.

Various IAOM processes are dynamically integrated with the ADNOC corporate database to fetch the various well and facility measurement in real-time. The process starts with the well test parameter validation in the IAOM system to ensure that validated parameters are updated within a well model. This process makes sure that the validated models can be utilized for the further optimization scenario and forecasting scenario to support the business plans.

The IAOM processes were implemented throughout a large asset with multiple fields encompassing different lift types, including natural flow, gas lift, and ESP. Automatic validation and in-built management-by-exception methodology reduced the requirement for engineering analysis significantly in various workflows such as almost 70% reduction of analysis time in production test validation and almost 95% reduction in the well technical rate determination. Moreover, the estimation of the production capacity scenario was almost 98.8% accurate with respect to the real field measurement. Such a level of accuracy enhanced the confidence in the model estimation and hence the production forecasting scenario was carried out to make sure that the business plans can deliver the desired production target.

Such an all-inclusive integrated process allowed the identification of true field potential and hence the full utilization of various work processes discussed in this paper. The exception-based approach helps the engineers to focus on engineering problems rather than just data validation.