Fluid Properties and Phase Equilibria (PVT)


Disciplines: Reservoir

Course Description

This (PVT) class will focus on the advanced and key topics of reservoir fluid properties, fundamentals, practical measurements and workflows. In the class, we will emphasize use cases and various examples including modern PVT report reviews as well as the key use-case related elements of equation of states (EOS s) that are often shared in our industry, especially in relation to reservoir models and other tools that use the PVT data. In addition, we will give a broad view of the new developments in all elements of the development cycle, including exploration, reservoir and production management, EOR/IOR and even CO2 sequestration. As the complexity of fluids and the reservoir conditions become more challenging, progress in the computational area is also being made, such as, new EOS models and computational techniques, advanced characterization methods, etc. Therefore, complex fluids and their implications will be inherently part of this class. One of the new topics that we will also introduce is the use of data-centric/machine learning methods in the area of hydrocarbon fluid properties

  1. Introduction
    • Why do we need fluid data: well testing, in place volumes, material balance equation, etc
    • Classification of Reservoir fluids: Black oils to volatile fluids to dry gases and Volumetric/PVT experiments
  2. Computational Aspects
    • Black oil & gas correlations, Definitions: API, SG (gas & oil), Bo, Rs, Pbp, Gas Gravity, Z-factor etc.
    • Machine learning and data-centric models
    • Fluid Properties Fundamentals ("Thermodynamic Aspects"- EOS formulas, underlying assumptions, reasoning etc), and HC characterization: SCN groups & implications
    • EOS Applications and their use
  3. Introductory Examples/Exercises: Compositional Data and Fluid Characterization
    • Review of modern PVT reports & QC: Essential data/experiments
    • Data Use: Measured data/Key data
    • CN distribution and its implications
  4. QC and Tuning (Recipe/Methodology): Justification and how to start tuning process
    • Exercises (oils and condensates): Various classes of fluids/report formats – (instructor driven), Tuning/Regression, Interfacing with other packages
  5. Compositional Grading
  6. OBM Contamination
    • OBM Contamination and decontamination
  7. Viscosity models 
  8. Emulsions
  9. CGR Correlations and Applications
  10. New Developments: Miniaturization, Pore Proximity, Life Cycle Management, MD, Data Driven/Hybrid Models (time permitting)
  11. MMP/MME: interaction of phase behavior and flow (time permitting)

Course Objectives:

Objective is to enable the participants with the following skills:

  • Being able to understand basic PVT data and needs assessment
  • Sampling and sampling related complexities
  • Landscaping of the current tools and techniques that are being used

General Objectives (repeated in the value statement as well):

  • To provide the Petroleum Engineers with the skills to use appropriate fluid models in various applications, in the light of modern software and interpretation approaches
  • In the area of Petroleum Engineering applications: to be able to ask the right question(s)

After the course we expect the participants:

  • To have a general understanding of EOS & its strengths and shortcomings
  • To be able to understand & QC routine PVT reports

Learning Level

Intermediate to Advanced

Course Length

2 days

Why Attend

They can use the outcome/learnings right away for their day to day work. In addition, the justification for the data acquisition and/or filling the gaps in the data and being able to assess the current and future needs will be quick wins for the participants. In addition, we will share info on the new progress made in various fronts in this line of business.

General Objectives:

  • To provide the Petroleum Engineers with the skills to use appropriate fluid models in various applications, in the light of modern software and interpretation approaches
  • In the area of Petroleum Engineering applications: to be able to ask the right question(s)

After the course we expect the participants:

  • To have a general understanding of EOS & its strengths and shortcomings
  • To be able to understand & QC routine PVT reports

Who Attends

As PVT is one of the pillars of Petroleum Engineering however the below individuals will benefit the most from the course:

  • Reservoir Engineers
  • Production and Facility Engineers
  • Pipeline Eng
  • Flow Assurance Engineers
  • Geochemists
  • Petrophysicists
  • Production geologists
  • Other subsurface engineers and scientists who deal with fluid properties and their applications

CEUs

Attendees will receive 1.6 CEUs for attending this 2-day course.

Cancellation Policy

All cancellations must be received no later than 14 days prior to the course start date. Cancellations made after the 14-day window will not be refunded. Refunds will not be given due to no show situations.

Training sessions attached to SPE conferences and workshops follow the cancellation policies stated on the event information page. Please check that page for specific cancellation information.

SPE reserves the right to cancel or re-schedule courses at will. Notification of changes will be made as quickly as possible; please keep this in mind when arranging travel, as SPE is not responsible for any fees charged for cancelling or changing travel arrangements.

We reserve the right to substitute course instructors as necessary.

Instructor

None

Dr. Birol Dindoruk is currently American Association of Drilling Engineers Endowed Professor of Petroleum Engineering at University of Houston, previously he was the Chief Scientist of Reservoir Physics and the Principal Technical Expert of Reservoir Engineering in Shell focusing on areas of Fluid Properties and CO2/Gas Injection Processes.
 

His technical contributions have been acknowledged with many awards during his career, including SPE Lester C. Uren Award (2014), Cedric K. Ferguson Medal (1994), and Distinguished Membership. In 2017, he was elected as a member of the National Academy of Engineering for his significant theoretical and practical contributions to enhanced oil recovery and CO2 sequestration.
 

He was one of the Distinguished Lecturers of SPE for 2010-2011 term.
 

Dr. Dindoruk was a Data Science and Engineering Analytics Technical Director of the SPE and a member of the Advisory Committee of the SPE Reservoir Dynamics and Description Technical Discipline. He has been active in various editorial positions under SPE and also Elsevier. Currently he is the Editor In Chief for all SPE Journals and as well as Editor In Chief of Journal of Natural Gas and Engineering of Elsevier.
 

Dr. Dindoruk is well-known for his extensive work on thermodynamics of phase behavior/EOS development and experimental work, interaction of phase behavior and flow in porous media, enhanced oil recovery and CO2 sequestration, and correlative methodologies.
 

Recently, Dr. Dindoruk has also been working in the area of data analytics, artificial intelligence, and machine learning and focusing on effective incorporation of data sciences into the oil and natural gas industry practices and energy systems. In recent years, he has authored/co-authored various articles for hydrogen, geothermal systems and adsorptive storage.
 

Dindoruk has 28 years of industrial experience, holds a BSc Degree from Technical University of Istanbul in Petroleum Engineering, MSc Degree from The University of Alabama in petroleum engineering and also a PhD from Stanford University in Petroleum Engineering and Mathematics, and an MBA from University of Houston.