Oil & Gas Industry Experience

Oil and Gas Industry Experience

Summary

I have done business requirements analysis, functional requirements analysis (logical design), development of software systems, testing, deployment and maintenance of many computer applications/systems in the oil and gas industry.

At Essochem Europe, i helped with the scheduling of the production of polymers.

At the Esso Belgium refinery I have implemented many computer applications regarding crude oil receipts, management of fuel orders and fuel deliveries, quality management systems and management of fuel trucks. Regarding the Liquefied Petroleum Gas (LPG), I have implemented an Operations Research model to determine the optimal location of two gas depots in Belgium.

At Exxon, Florham Park, NJ I have developed a system to manage the energy conservation of heat exchangers in the refinery. At Exxon Research and Engineering, Clifton, NJ , I used a decision risk analysis tool to predict the expected value (revenue) of licensing patents, of patent royalties and of investments in certain refinery enhancements.

Production of Polymers

I modeled the production of polymers. Using this mathematical model I determined the optimal start time for production batches as a function of set up time, run time, and of required resources such as machines, labor and tools.

Crude Oil Refinery Applications for Transactions

Managing crude oil receipts
- I have developed a computer/software application to record the receipts of crude oil that was delivered via a pipeline from Amsterdam, The Netherlands to the Antwerp refinery in Belgium. The application estimated also the quantity of crude oil that was still in the pipeline after the pipeline valve was shut in Antwerp, Belgium. This was programmed in PL/1 using a Total database.
Managing fuel orders and fuel deliveries
- I have developed a computer/software application to extract hourly and daily quantity averages of fuel deliveries from the refinery process control system. The fuel was delivered to the fuel distributors and Esso gasoline stations. These deliveries were compared with the fuel sales orders.
Fuel Quality Management System
- The actual specification values were extracted from the refinery process control system for the different types of fuel. These actual values were compared with the standard specification values. For instance if the actual octane for regular gasoline was 95 versus the standard value of 87, there was a quality give away of 8 octane. Other specification values were checked for flash point, viscosity, etc.
Management of Fuel Trucks
- The management system listed the trucks, their capacity, their routes, their trips, their maintenance schedule, their drivers, the inspection dates of the trucks, and the availability of each truck.
Optimal Depot Location for LPG
- I used an Operations Research model to determine the optimal location of two LPG depots in Belgium. It considered the travel distance to sets of customers, the travel time, the truck capacity, the delivery quantity to each customer and the revenue from each customer. The result was impressive.

Managing the Energy Conservation of Heat Exchangers at the Refinery

I have developed a computer system to capture the produced BTUs of heat exchangers from the process control system of a refinery. The system captured also the BTUs that were recycled from the heat exchangers and reused by heat exchangers. This helped to pinpoint the heat exchangers that had a too low recycling percentage.

Decision Risk Analysis of Refinery Investments

I used a decision risk analysis tool to determine the expected value/revenue of licensing a patent ot others, of buying a license, of patent royalties, and of investments in refinery improvements. Probabilities were assigned to all the scenarios. This tool considered many factors such as the live span of the patent, the price of external licenses, the value of using the external license, the licensing of patents by competitors, and the new technology that will be used at certain times in the refinery. The expected revenue streams were quite on target for the scenarios that were implemented. This is quite a powerful tool.