SPE-181024Recovery Factor Prediction for Deepwater Gulf of Mexico

Oilfields by Integration of Dimensionless Numbers and

Data Mining Techniques

Priyank Srivastav 1, Xingru Wu 1, Amin Amirlatifi 2, Deepak Devegowda 1,

Saman Hajirezaie 3

1 University of Oklahoma

2 Mississippi State University

3 University of Aberdeen

Field Analogs

Material Balance

Reservoir Simulation

History Matched

Simulation Models

Why Data Mining for Recovery Factor Prediction? Slide 2

SPE-181024• Recovery Factor Prediction for GOM using Dimensionless Numbers & Data mining • Saman Hajirezaie

Data Mining

Outline Slide 3

SPE-181024• Recovery Factor Prediction for GOM using Dimensionless Numbers & Data mining • Saman Hajirezaie

Initial Intuition

Mathematical Demonstration

Proof of Concept

Part-I : Introduction

• Problem Statement

• Geological Set-up of Gulf of Mexico

Part-II : Data Mining Algorithms

• Clustering and Regression algorithms

Part-III : Dimensionless Reservoir Models

• Scaled Reservoir Models

• Conclusions

Problem StatementSlide 4

SPE-181024• Recovery Factor Prediction for GOM using Dimensionless Numbers & Data mining • Saman Hajirezaie

• Classification of Different Fields and its

characteristics.

• Generating easy to use universally applicable

correlation for Recovery factor