Oil and Gas Production Data Analysis with MATLAB

Overview

In this session, we will demonstrate how MATLAB can help streamline production data analysis workflows. The demo covers a wide range of topics, from pre-processing of oil and gas production data from public repositories to economic analysis and standalone app deployment with App Designer and MATLAB Compiler. The key message of this demo is that MATLAB offers different tools and programming techniques that can help users streamline complex data analysis workflows and deploy these artifacts with Web App Server. We also demonstrate how the Live Script used for this analysis can be converted into a standalone MATLAB App that can be shared with other team members. This app features more advanced functionality, such as export analysis results in CSV format. The demo will be divided into four sections:

Highlights

• Import Unstructured Production Data. We show how to pre-process production data from the Texas Railroad Commission using a custom function generated by MATLAB.
• Create a Custom Regression Model. We use the Curve Fitting Toolbox to create a custom predictor for production rates. The regression model and some additional routines were packed into a MATLAB object so that users are free to create as many well objects as needed without needing to go through the regression process every time.
• Oil and Gas Production Forecasting. Like in the previous step, we create a forecast object to handle the prediction of future oil and gas rates as well as cumulative production. As such, users can create as many forecast objects as needed.
• Petroleum Economics Analysis. The last part of the workflow shows how to calculate economic metrics using production forecast objects. Here, the user can specify average oil and gas prices which can be randomized, tax rates, and other royalty fees. Similar to the previous steps, we define an economics object that users can use to evaluate different production scenarios with a single forecast object.

About the Presenter

Oscar Molina Ortiz is a Senior Application Engineer from the MathWorks with extensive experience on solving key business issues in petroleum engineering using applied mathematics and computer science. He has a solid background in traditional reservoir simulation, geological CO2 storage simulation, pressure and rate-transient analyses, production optimization, computational fluid dynamics, and finite element analysis. Oscar holds a BS degree in Mechanical Engineering, MS and PhD degrees in Petroleum Engineering and is currently pursuing his MS degree in Computer Science.