ali

International Research: Novel Model for Oil Flow Rate Estimation

Publication Overview

  • Paper Title: A Novel Model for Estimating Oil Flow Rate Through Wellhead Chokes in an Iranian Heavy Oil Field.

  • Publisher/Index: SSRN (Elsevier) & IEEE Conferences.

  • Date: 2022

  • Focus Area: Production Optimization & Heavy Oil Fluid Dynamics.

  • Methodology: Numerical Simulation & C# Programming.

The Strategic Value

“Revolutionizing production management in heavy oil reservoirs through high-precision computational modeling.”

This research bridges the gap between software engineering and petroleum production, offering a low-cost, high-accuracy alternative to expensive metering hardware.

 

The Mission: Why This Research Matters

One of the primary responsibilities of a Production Engineer is to maintain reservoir health and ensure sustainable production (“Sayanati” production) through the precise control of Wellhead Chokes.

The Problem:

In Iranian heavy oil fields, the fluid viscosity renders classic empirical models (like Gilbert or Ros) highly inaccurate.

The Solution:

I conducted this research to solve this specific challenge by developing a localized, native algorithm. The goal was to empower engineers to estimate flow rates with minimal error without relying on expensive, high-maintenance real-time multiphase flow meters (MPFM).

Technical Deep Dive: Engineering Meets Coding

In this paper, I analyzed a robust dataset comprising 180 real-world field tests from 5 distinct wells. My methodology included:

  • Algorithm Development (C#): I personally coded a custom solver using C#, utilizing the Gauss-Jordan Elimination Method to solve complex multi-variable linear equations.

  • Heavy Oil Analysis: I investigated the simultaneous impact of critical parameters—Wellhead Pressure (WHP), Choke Size, Temperature, and BS&W (Basic Sediment & Water)—on the final flow rate.

  • Advanced Simulation: Integrated Schlumberger PIPESIM software to model well placement patterns and analyze pressure drops across flowlines.

The Proof: Superior Accuracy & Optimization

  • Drastic Error Reduction: My proposed model achieved an Average Relative Error of just 5.8%.

    • Context: Traditional models frequently yielded errors as high as 28% for this specific fluid type.

  • Lifecycle Extension: By applying this model to historical data (2006–2013), I demonstrated how optimal choke sizing directly correlates to controlled production decline and extended reservoir life.

  • Global Standard: The research adheres to strict international standards and is indexed in prestigious databases like IEEE Xplore and SSRN.

Verification

Authors: Milad Shayanmanesh (Science and Research Branch, IAU) & International Research Team.

Indexing: SSRN / IEEE.

Classification: Original Research Paper (Numerical Simulation & Programming).

Status: Published & Indexed.



Download PDF Paper

/by