This course will provide the basics of carbonate reservoir description for the less experienced staff (covered in 2 days), followed by 3 days of more advanced material. The last 3 days will address the road map (workflow) and best practices used in data preparation and data analysis to build a coherent 3D static model of the reservoir.
Course Level: Skill Duration: 5 days Instructor: Jorge S. Gomes
Designed for you, if you are...
A geologist, petrophysicist, geophysicist or reservoir engineer
The course assumes some basic geoscience and engineering knowledge. No prior hands-on experience of 3D modelling is required.
How we build your confidence
In the first 2 days the instructor provides the basic geological, petrophysical and core analysis background for reservoir characterisation and in the following days the instructor works with workflow examples applied to field data, using PowerPoint slides (no 3D modelling software used in class) in order to illustrate how the data was analysed and processed to build a static model. In the last day the instructor shows several examples of 3D models (deterministic and stochastic) and will illustrate good practices and anomalies.
The benefits from attending
At the end of the course, you will have the background knowledge to understand the role of reservoir description in 3D modelling, you learn how to check the key input parameters and assumptions used in modelling, so you can confidently evaluate the quality of 3D static models used for field development planning. The course will address the probabilistic distribution of hydrocarbons in place (P90, P50 and P10), and touches on the upscaling process, a requirement for fast flow simulation studies. In particular you will understand how to:
Use geological and petrophysical information to understand the depositional environments and the diagenetic processes that affect the rock fabric.
Characterise the reservoir rock types using several techniques such as mercury injection capillary pressure (MICP), NMR and SCAL data.
Understand the important role of a geological framework with a zonation scheme that honours flow units (use of PLT/RST/TDT for validation) within a sequence stratigraphic framework.
Understand the role of 3D seismic data and faults in the reservoir framework and in the property modelling.
Understand the difference between deterministic and stochastic algorithms to propagate continuous (petrophysical) properties and discrete variables (facies, rock types) in the inter-well region.
Understand the importance of capillary pressures by rock types and fluid contacts (FWL, OWC) in the calculation and validation of saturation models used for volumetrics (STOIIP).
Participants also learn the difference between resources and reserves and their respective uncertainties (High and Low estimates; P90, P50, P10).
Understand how to rank realisations and perform averaging and upscaling of properties.
Basically, participants will learn how to integrate static and dynamic data in a coherent and consistent manner to build a static model.
Geological aspects: Review of sedimentology, depositional and diagenetic models and sequence stratigraphy.
Rock Fabric: Review of carbonate textures, pore systems, pore throat sizes and capillarity.
Petrophysical & seismic aspects: Review of petrophysical and seismic inputs required to reservoir description.
Lab Data: Detail explanation of capillarity effects and its use in rock fabric characterisation and SW modelling. Review of MICP, SCAL, NMR to qualify different rock fabrics.
Rock-fluid interaction: Review wettability, Kr curves, OWC-FWL differences and sensitivity analysis on saturation modelling (Leverett J function, Skelt-Harrison etc.).
Flow units: Review of zonation, layering, flow unit concepts, k/phi, FZI, Lorenz plots and the use of flowmeters for validation.
Geostatistics: Univariate and bivariate statistics, PDFs, CDFs, Cv and spatial statistics. Evaluate variogram models (Spherical, Exponential, Gaussian) and the effect of their parameters (range and nugget) on model outcomes.
3D modelling: Comparison of estimation and simulation approaches handling discrete and continuous data; inverse distance, kriging, collocated co-kriging, sGs, SIS and co-simulation techniques.
Monte Carlo simulation with computation of P90, P50 and P10 values.
Assessment of reservoir heterogeneity, averaging and upscaling techniques.