Datapages, Inc.Print this page

Click to view presentation in PDF format.

 

Conditioned Forward Stratigraphic Modeling in Large Carbonate Fields: A Dionisos Model of Karachaganak*

Miriam Andres, Phil Bassant, and Mitch Harris

 

Search and Discovery Article #40352 (2008)

Posted November 20, 2008

 

*Adapted from oral presentation at AAPG International Conference and Exhibition, Cape Town, South Africa, October 26-29, 2008.
Click to view list of articles adapted from presentations by P.M. (Mitch) Harris or by his co-workers and him at AAPG meetings from 2000 to 2008.

 

Chevron Energy Technology Company, San Ramon CA ([email protected]; [email protected]; [email protected])

 

Abstract

Karachaganak is a large Devonian to Permian age isolated carbonate retrograde gas-condensate field in Northern Kazakhstan. Here, conspicuous steep (20-30 degrees) high-rise (<400 m) clinoforms are observed yet un-mapped due to poor seismic expression, and thus not integrated into the conventional geocellular model used for flow simulations. Although sufficiently simulating field-scale behavior and long-term production, this approach inadequately addresses individual well-performance as proportional bedding used in the conventional model construction cross-cuts steeply dipping flow units. Flow-unit orientation is critical as it strongly influences vertical reservoir connectivity, affecting produced-fluid composition which varies vertically in the reservoir. Steeply dipping flow units can also decrease horizontal transmissibility (flow across multiple flow units), leading to lateral variations in pressure which are merely the result of stratigraphy.

To address the above-mentioned challenges, we build a model using ‘Dionisos, a diffusion-based forward stratigraphic modeling package. Vertical thicknesses are conditioned by stretching the final model to mapped seismic surfaces. Facies are conditioned manually to interpreted facies maps by interval. Equally, geomorphologic elements of platform-top and slope are conditioned to seismic observations. Boundary input parameters, such as model age, eustatic sea level, as well as sediment production rates and depths, correspond to the respective geologic age of the reservoir. The resulting S-grid is populated with depositional facies and captures the non-stationary facies patterns currently difficult to achieve with conventional geostatistical simulations. 3D co-rendering of the Dionisos model and seismic cube has provided a powerful instrument used extensively to re-evaluate the seismic interpretation. We gained valuable insights in particular where model prediction and seismic cube disagree and in areas of poor seismic quality, such as sub-salt environments. Furthermore the model offered alternative scenarios to existing seismic interpretations.

 

uAbstract

uFigures

uFSM

uFSM workflow

uInterrogation summary

uKey results

uReferences

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

uAbstract

uFigures

uFSM

uFSM workflow

uInterrogation summary

uKey results

uReferences

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

uAbstract

uFigures

uFSM

uFSM workflow

uInterrogation summary

uKey results

uReferences

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

uAbstract

uFigures

uFSM

uFSM workflow

uInterrogation summary

uKey results

uReferences

 

Forward Stratigraphic Modeling (FSM)

  • Numerical simulation of the sedimentological processes that produce stratigraphy.
  • Numerous modeling software packages available; each with a distinct specialty (i.e., time and spatial scale, geologic setting, etc.).

DIONISOS —Diffusive Orientated Normal and Inverse Simulation of Sedimentation (by IFP -- Granjeon, 1997; Granjeon and Joseph, 1999)

  • diffusion-based, multi-lithology, 3D simulator for the use of basin to sub-basin scale over millions of years
  • open structure which can model clastics, carbonates, mixed systems, deep water, slope processes, etc.
  • will not model individual objects (i.e., sand bars).

FSM Workflow

  1. Choosing critical input parameters
      -rate of subsidence -> accommodation space
      -rate of sea level change -> accommodation space
      -sediment production rates -> strata thickness
      -hydrodynamic regime -> sediment distribution
      -model dimensions, time step; model space
      -conditioning of facies and geomorphologic elements
  2. Build initial model and perform sensitivity analysis.
      -identify critical parameters and their effect on model.
  3. Build, interrogate and revise base model.
      -comparison to data (seismic and facies at wells)
      -model reruns to fine tune facies match

Model Interrogation Summary

  1. Test the geological validity of the model by comparing with:
    • facies at wells
    • observed seismic geometries
    • internal consistency check between facies and bedding architecture.
  • overestimation of shallow-water platform
  • significantly more slope facies needed
  • variable clinoform dips
  • in need of alternative progradation style
  1. Decide whether the model is:
    • geologically valid as is,
    • needs updating before use,
    • or belongs in the bin.
  2. Revise base model.

Key Results

Established workflow for ‘conditioned’simulation

  • revised conceptual understanding of reservoir architecture
  • investigated extent of slope versus shallow platform facies
  • improved our understanding of clinoform characteristics
  • reservoir-quality/facies prediction in poorly imaged areas

Common visualization and communication tool.

Selected References

Bassant, Phillip, and Paul M. (Mitch) Harris, 2008, Modeling Reservoir Architecture of Isolated Carbonate Platforms: Search and Discovery Article #40294 (http://searchanddiscovery.com/documents/2008/08070bassant/index.htm).

Bassant, Phillip, and Paul M. (Mitch) Harris, 2008, Analyzing Reservoir Architecture of Isolated Carbonate Platforms: Search and Discovery Article #40295 (2008) (http://searchanddiscovery.com/documents/2008/08071bassant/index.htm).

Granjeon, D., 1997. Modelisation stratigraphique deterministe - conception et applications d'un modele diffusif 3D multilithologique: Memoires Geosciences Rennes, Ph. D. Dissertation, Geosciences Rennes, Rennes, France, 189 p.

Granjeon, D., and Joseph P., 1999, Concepts and applications of a 3D multiple lithology, diffusive model in stratigraphic modeling, in J.W. Harbaugh et al., eds., Numerical Experiments in Stratigraphy: SEPM Special Publication 62, p. 197-210.

Return to top.