|OG228||01 - 05 Sep 2019||Dubai - UAE||4,950|
*All fees are exclusive of VAT
Why Choose this Training Course?
This interactive PetroKnowledge training course will highlight the importance of data integration from a variety of sources to address complex reservoir evaluation and productivity challenges experienced throughout the full asset life cycle.
This PetroKnowledge training course will cover a variety of data sources, fundamentals of reservoir characterisation, and methodologies of integrating key information. The course combines theory with practical exercises to give participants a working knowledge of how integrating available data at various scales can be used to evaluate reservoir quality, heterogeneity and improve the productive potential to maximize recovery of hydrocarbons.
This training course will feature:
- Principles of rock and reservoir properties
- The value of different data sources and purposes of data acquisition for reservoir analysis
- Integration of core and log data to characterise flow units and reservoir properties
- Provide hands on experience using field examples to evaluate complex reservoir conditions
- Give advice regarding common pitfalls of data acquisition, interpretation and presentation of results
What are the Goals?
By the end of this training course, participants will learn to:
- Understand the benefits of data integration
- Understand various sources of data and the purpose of data acquisition
- Plan data acquisition programmes and oversee core handling and preservation techniques
- Understand the role of routine and special core analysis in reservoir characterisation
- Deduce reservoir properties from log interpretation and core analysis
- Integrate reservoir and well data to provide an evaluation of the reservoir and characterize flow units
- Avoid common pitfalls of data acquisition and analysis
- Present and manage data appropriately
Who is this Training Course for?
This training course is suitable for a wide range of professionals who have a basic understanding of petrophysics, geology, engineering and need a more advanced course covering how to integrate different data sets together to gain an improved understanding of reservoir performance.
- Well Site Geologists
- Reservoir Engineers
- Production Engineers
- Drilling Engineers
- Data Managers
- Oil and Gas Industry Professionals involved in logging data interpretation and validation
How will this Training Course be Presented?
This training course will present methodologies to integrate the various data types in conjunction with a number of exercises combined with field examples in a workshop format to enhance the learning and knowledge of the participants.
Personnel will be able to:
- Plan improved data acquisition programs
- More effectively assess wider data sets for the benefit of a range of asset types
- Work more effectively in a multi-disciplinary team and manage third party contractors.
- Appraise existing data sets and evaluations with the aim of reducing In-Place volume uncertainty
- Develop and build on existing knowledge of the collection and interpretation of core, log and test data
- Learn the principles of data acquisition planning and be able to identify the best combination of tests and techniques for an optimal analysis programme
- Gain an understanding of the pitfalls of the various data types and their potential implications.
- Raise self-assurance in evaluating previous studies.
- Provide confidence in managing third party relationships
Day One: Introduction and Reservoir Properties
- Overview of the need for integrated data analysis – advantages and disadvantages
- Overview of the various data types and sources (well log, core and fluid samples etc)
- Refresh rock properties (porosity and permeability)
- Basic Fluid properties
- Pressure and temperature gradients
Day Two: Data Acquisition and Description
- Wireline logs – an overview of key log types including gamma ray, spontaneous potential, resistivity, caliper, Neutron-density and image logs.
- Acquisition planning
- Best practice for log data
- Coring – an overview of whole and sidewall core logging
- Acquisition planning
- Core handling and preservation – core orientation
- Best practice for core data
- Formation Tests – MDT and RFT
- Acquisition planning
- Exercise: Analysis of data types and plan data acquisition
Day Three: Data Preparation
- Core Data
- QC core data and bias check
- Preliminary zonation determination
- Routine Core Analysis (RCA)
- Special Core Analysis (SCAL)
- Log Data
- Log preparation audit and normalization, data conditioning
- Environmental corrections
- Lithostratigraphic and chronostratigraphic correlation
- Log and Core synchronisation – lag determination, logging cuttings and core to correlate with the log suite
- Well Test Interpretation
- Drill stem testing – reservoir scale fluid pressure and mobility, fluid return and flow dynamics
- Wireline and LWD formation testing – fluid extraction, downhole chemical analysis, sample return, mobility and flow dynamics
- Pressure transient analysis
- Exercise: Core, log and well test inspection and QC
Day Four: Integration of Data, Analysis and Interpretation
- Core Analysis
- Core description and logging
- Integration of RCA with core
- Assimilation of SCAL techniques to evaluate capillary pressures, wettability, petrophysical properties (m, n), saturations, permeability, rock strength, stress / strain
- Log Analysis
- Basic Log Analysis – compute Vsh, porosity, Sw, K, Netpay
- Common pitfalls of basic log analysis
- Well test interpretation to assess well productivity and production issues
- Integrate well tests and production logging data
- Determination of hydrocarbons in place
- Water and gas coning effects
- Contact evaluation
- Exercise: Integration of core and log data for porosity and permeability calculations, scale up of permeability and calibration, evaluation of well productivity
Day Five: Data Presentation, Sensitivity Studies and Next Steps
- Data set pitfalls
- Resolution of lateral and vertical heterogeneity
- Scaling issues between reservoir field scale (DST), logging scale and detailed laboratory testing.
- Managing Uncertainty
- Recalculation sensitivity studies – evaluating existing studies
- Effects of uncertainty on In Place volumes
- Reporting of results
- Data presentation and database management
- Data formats for integration
- Data hierarchy
- Next steps
- Integration of core, log and test data for use in reservoir modelling
- Further analysis options