Steady-state nodal analysis is still the core tool for understanding how a well's inflow and outflow behave together. But getting real value out of software like PIPESIM or PROSPER takes more than knowing the interface — you need a solid grip on multiphase flow correlations, fluid modeling, and where the bottlenecks in your system actually sit.


In this hands-on workshop, Nashat Jumaah Omar walks you step by step through building, calibrating, and optimizing production systems, and shows you how to construct nodal plots to diagnose and optimize flow from oil and gas wells.

Workshop Objectives

Model setup and fluid characterization (PVT)


Inflow Performance Relationship (IPR) construction and validation


Multiphase flow correlation selection and VLP matching


Single-well nodal analysis and bottleneck identification


Wellhead choke sizing and artificial lift integration (gas lift / ESP)


Sensitivity analysis and production rate optimization


Network modeling and surface facility coupling


Gas hydrate risk prediction and wax deposition mapping

About the Presenter

Nashat Jumaah Omar is a production engineer, instructor, and technical consultant with over 11 years of experience in the oil and gas industry, with particular depth in production engineering, flow assurance, subsurface workflows, and engineering data applications. His work combines petroleum engineering knowledge with practical use of digital tools such as Python, SQL, Power BI, C#, FORTRAN, and VBA to improve analysis, automate repetitive tasks, and support more efficient engineering workflows.


Over the course of his career, he has worked across production operations, well and network modeling, flow assurance, production data management, and software-enabled engineering solutions, including experience with platforms such as PIPESIM, PROSPER, OLGA, and OFM. His professional background also includes training and mentoring engineers in Python, machine learning, data analytics, and applied digital workflows for upstream oil and gas environments


At Petroleum Engineers Association, he has contributed to the design and delivery of technical training programs for petroleum professionals, including courses in Python for petroleum engineering, machine learning, data analysis, and production and reservoir applications. His teaching style is grounded in real industry use cases, with an emphasis on helping participants translate coding and analytics concepts into practical tools for day-to-day engineering work.

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Material Balance Modeling
November 28, 2026 - November 29, 2026
Material Balance Modeling

Material balance is one of the most direct methods available to a reservoir engineer for estimating hydrocarbons in place, identifying the drive mechanism and forecasting reservoir performance. It requires far less data than a full numerical model, and when it is set up correctly it produces results that can be defended in technical reviews and reserve audits.This workshop covers the complete material balance workflow as it is applied on producing assets. It begins by placing the reservoir within the integrated production system, then moves through data preparation and quality control, tank model construction, drive mechanism identification, and the use of analytical and graphical diagnostic tools. Participants work through the classical diagnostic plots, including Dake and Campbell, and learn how to read what each plot indicates about depletion, gas cap expansion and water influx.The second part of the workshop addresses history matching using both analytical and graphical techniques, determination of STOIIP, aquifer identification and sizing, and running prediction cases to generate production forecasts and recovery estimates. Results are compared against volumetric and simulation-based estimates so that participants understand where material balance is reliable and where a numerical model becomes necessary.The workshop is delivered at an advanced level and is intended for engineers who already work with production and pressure data and want a structured, repeatable method for in-place volumes, drive mechanism evaluation and performance prediction.