• Introduction to geomodeling (geological, geophysical, petrophysical and RE data integration)
• Review on descriptive and inferential statistics, data analysis and data transformation.
• Geostatistics, stationarity and concept of spatial heterogeneity; variogram calculation, setting and modeling; anisotropy, directional analysis and cross variogram.
• Unsample locations and estimation methods (simple – ordinary – universal kriging, co-kriging, collocated co-Kriging) and simulation method (TGS, SIS, Object-based, SGS, etc.).

• Fault network (complex structure, reverse fault, numerous fault; fault truncation, etc.).
• Interpreted vs. calculated horizons; horizon modeling and data filtering.
• Horizon truncation and onlapping.
• Zonation and layering (isochore correction).
• 3D grid concept (pillar, non pillar, zone, subgrid, staircase, etc.).
• Review of carbonate conceptual geology, depositional environments and reservoir quality.
• Facies interpretation (core interpretation, log – core calibration, facies interpretation in un-cored wells, etc.)

• Structural data loading (horizons and fault sticks/picks).
• Structural data QC, cleaning and filtering.
• Building integrated structural modeling (fault model and horizon model).
• Built zonation based on sequence stratigraphic picks.
• 3D grid construction and optimization (grid size and orientation) to yield stable structural model.
• 3D grid cell thickness optimization and preserving statistical characteristics and geological feature; layering setting in carbonate with and without diagenetic overprint.

• Identify parasequence surfaces and system tracts.
• Argillaceous content-based correlation in carbonate reservoir and sequence stratigraphic correlation.
• Identification of diagenetic overprint in log/cell resolution and its impact in 3D model
• Combining argillaceous and diagenetic process in log correlation, preserving geological heterogeneity

• Lithofacies interpretation, grid scale resolution and vertical facies associations/regrouping.
• Core – log calibration to generate genetic facies group on wells; facies interpretation on un-cored wells.
• Object-based and SIS techniques in genetic facies modeling.
• Data analysis and volume fraction; honoring volume fraction analysis in facies modeling.
• Modeling genetic facies, conceptual and seismically guided techniques.

• Petrophysical-based rock typing (porosity based, porosity-Sw based and porosity-permeability based).
• RFN calculation and rock typing classification based on core and log data (if applicable).
• RQI/FZI calculation and rock typing classification based on core and log data (if applicable).
• Modeling rock-types with SIS technique bias to facies model, with and without seismic attributes, application of cross variogram from seismic attribute and log data.
• Combine rock types model with diagenetic overprint in carbonate (if any).
• Selecting appropriate rock-type models.

• Log data import and QC.
• Vshale modeling; log upscaling with/without rock type bias, data analysis and transformation, variogram setting and modeling and SGS modeling technique with seismic attributes, application of cross variogram from seismic attribute and log data
• Porosity modeling; log upscaling bias to rock type, data analysis and transformation, variogram setting and modeling in each rock type; and SGS modeling technique with and without seismic attributes, application of cross variogram from seismic attribute and log data.
• Dilemma of NTG concept, determination and cut-off; do we need to model NTG?

• Log data import and QC.
• Porosity – permeability cross plotting (direct cross plotting from porosity or from porosity-Vshale) and permeability model transformation.
• Calculating permeability multiplier based on well test KH and calibrating permeability model.
• Sw calculation based on Pc (Leverett-J Function), determination of FWL and contact based on MDT/RFT.
• Sw calculation in 3D grid model.

• Volumetric calculation.
• SKK Migas method on volume calculation (P1, P2 and P3 based on well tests) and risked volume category.
• Uncertainty setting; SEED number, fluid contact, petrophysical range, etc.
• Monte Carlo uncertainty and sensitivity analysis running.
• Presenting uncertainty and sensitivity of the model.

• Model validation; visual and statistical (histogram and variogram of data vs. model)

Static 3D Modelling in Clastics Depositional Environment is set for Geoscientists and petroleum engineers responsible for conducting comprehensive reservoir studies. Prerequisites: Petroleum engineering or geoscience background with experience in reservoir studies.

Trainer with 20-years international experience in oil and gas industry as specialist in Geomodeling/Development Geology. Able to utilize Geoscience’s applications from Schlumberger, Halliburton, Roxar to yield a strong analysis and interpretation of geosciences. It is including sedimentology and sequence stratigraphy, geological modelling and geostatistics (deterministic to stochastic modeling from structural, facies, property, up-scaling, volumetric and uncertainty through well planning), fracture modelling, reservoir characterization and risk analysis in both siliciclastic and carbonate reservoirs. Have a good understanding of petroleum engineering and petroleum economics, including field development plan, production and operational support. Also have a broad experience in lecturing and course guiding (development geology, geomodeling and geostatistics).

This Static 3D Modelling in Clastics Depositional Environment Training will be held several times in Indonesia throughout 2022 with minimum 5 participants and maximum 15 participants.

The deliverables during the course includes:

• Modules
• Training Certificates
• Comfortable Classroom & Training Kits (if offline)
• Training Recording (if online)