DL Series: Waterflood Optimisation benefits by Data Analytics on Mature Fields

This is a Distinguished Lecture Series - Exclusive for SPE Members registered in the Northern Emirates Section.

Title : Distinguished Lecture Series :  Waterflood Optimisation by Data Analytics on Mature Fields Accelerated the Field Developing Process from Months to Weeks

Presenter : Babak Moradi

Agenda

• 430 pm - 5  pm : Check in - Pre networking 
• 5 pm - 6 pm : Technical session
• 6 pm onwards : Group photo and networking 

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Synopsis 

Currently, 70 percent of global oil is being produced from mature fields. The waterflood process is widely used to improve the oil recovery of mature fields. Unlocking the potential of existing mature assets and the optimization of waterflooding can be challenging using traditional dynamic modelling workflows due to high well count, years of historical production data (extensive data set), complex stratigraphy, etc.; however, these challenges create opportunities for applying data-driven techniques. In addition, increased attention towards reducing carbon emissions makes data-driven techniques more attractive as they are computationally-light techniques.

First, this work reviews classical analytics for studying the waterflood process; after that, machine learning techniques are used to optimize rates of water injector wells for maximizing the production efficiency. Next, an innovative hybrid physics-guided data-driven method is presented to accelerate field development and locate the remaining oil (LTRO) process from months to weeks. The results of this new workflow are validated against outputs of the numerical simulation and 4D seismic info. Furthermore, the comparison of post drilling results and predictions of the new physics-guided data-driven workflow is presented for a field located in the Middle East.

This presentation demonstrates that it is now possible to deliver digital LTRO projects, capturing the full uncertainty ranges, including complex multi-vintage spatial 4D datasets, and providing reliable non-simulation physics-compliant data-driven production forecasts within weeks. This presentation addresses the challenge of reducing mature fields study resource intensity and therefore, time and costs whilst maintaining a high degree of fidelity.

Speaker background

Babak Moradi has over 13 years of experience in reservoir engineering. He has been involved in studies of more than 20 mature fields located in the Middle East, South East Asia, Australia, North Sea, and Africa. Babak is an expert in machine learning and programming; he has developed several software packages relating to petroleum engineering. He is the author of 30 scientific publications in areas of enhanced oil recovery, CO2 sequestration, fluid properties modelling, and has published a textbook on fluid flow in the wellbore. His strong background in mathematics and programming helps him to turn data into knowledge.