Audun Sektnan

This user manual describes the COHIBA surface modeling software. It consists of: Part I Introduction: Basic ideas and terminology Part II User manual: Usage, input data, and results Part III Tutorials: Special topics such as volumes, simulation, and faults Part IV Reference manual: Descriptions of all COHIBA model file elements Part V Theory: Methods used by COHIBA Part VI Appendix: Release notes, known issues, references, list of acronyms, tables and figures, and an index

This user manual describes the COHIBA surface modeling software. It consists of: Part I Introduction: Basic ideas and terminology Part II User manual: Usage, input data, and results Part III Tutorials: Special topics such as volumes, simulation, and faults Part IV Reference manual: Descriptions of all COHIBA model file elements Part V Theory: Methods used by COHIBA Part VI Appendix: Release notes, known issues, references, list of acronyms, tables and figures, and an inde

Stochastic facies models based on truncated Gaussian random fields are known for being flexible and well suited to reproduce patterns and features from analogues or conceptual models. In pluri-Gaussian simulation, the number of random fields is theoretically unlimited, which adds flexibility and makes it possible to model a wider range of geological settings. However, the truncation map traditionally used to set up these models quickly becomes unclear when used for higher dimensions. Hence, in practical pluri-Gaussian applications, the number of fields is typically kept as low as two or three. We present a formulation of pluri-Gaussian simulation in which the truncation rule, the function that maps combinations of Gaussian random field values to facies categories, is represented as a particular binary tree. This is used to decouple the fields in the critical Gibbs sampling step of the conditioning process in such a way that we can use multiple lower-dimensional samples instead of a single higher-dimensional sample. The resulting conditioning algorithm scales excellently with the amount of conditioning data and the number of fields. The algorithm accepts a combination of trends and probabilities in the same model setup, which provides additional flexibility in representing varying depositional geometries. We demonstrate the hierarchical pluri-Gaussian simulation with two practical examples. One is based on real data from the Volve oil field in the North Sea. The other combines a large number of synthetic observations with a truncation tree tailored to a more complex geological concept. The choices made when building the truncation tree affect the features of the realizations, especially when it comes to which facies can be in contact and which can overprint each other. This aspect of tree building is discussed in light of the numerical examples given.

We propose a smooth stochastic process for modeling the vertical well path uncertainty. This process describes the accumulation of measurement errors along the well path. We combine the stochastic process with a stochastic model for surfaces into a consistent framework for simultaneous prediction of well paths and surfaces. We show properties of the proposed stochastic process and provide examples of interaction between wells and surfaces.

Truncated Gaussian fields are a common way of modelling facies, where the correlation structure in the Gaussian field defines a spatial correlation structure for the facies. Plurigaussian simulation takes it further by using several underlying Gaussian fields. This allows more flexibility and makes it possible to model a wider range of geological settings, but conditioning can be difficult. We present a fast and accurate implementation of conditional plurigaussian simulation. Our approach has two key elements. The first is to combine complex truncation rules with input facies probabilities. The truncation rule, which is a function from the Gaussian fields to a facies value, can be represented neatly as a binary truncation tree. This allows for a general representation that includes all the traditional 2D truncation masks. We show how to combine the use of such trees with facies probabilities, even in complicated cases with more than two Gaussian fields. The second key element is correct conditioning to all facies observations, not just transitions, by treating them as inequality constraints on the Gaussian fields. We perform inequality Kriging by replacing these facies observations by synthetic observations of the underlying Gaussian fields. To generate synthetic observations that agree with the target posterior distribution, we use a Gibbs sampler. Since this is a quite slow algorithm, we take certain measures to make the calculations faster. Synthetic observations are then used in Kriging, improving the conditioning to facies logs from wells. We demonstrate the method with a synthetic case that combines a large number of observations with the use of a truncation tree tailored from a geological concept.

A COHIBA case study investigating a synthetic model for depth conversion, with focus on how to get the zonation right and the impact of different modelling settings on the estimation of volume distributions.

This user manual describes the COHIBA surface modeling software. It consists of: Part I Introduction: Basic ideas and terminology Part II User manual: Usage, input data and results Part III Tutorials: Special topics such as volumes, simulation and faults Part IV Reference manual: Descriptions of all COHIBA model file elements Part V Theory: Methods used by COHIBA Part VI Appendix: Release notes, known issues, references, list of acronyms, tables and figures, and an index Advanced topics and technicalities are marked by the warning symbol in the right margin. COHIBA model file elements marked by this warning symbol should be used with some care. The latest version of this document is available at: www.nr.no/COHIBA. For COHIBA support contact Pal.Dahle@nr.no or Ariel.Almendral.Vazque@nr.no. The following scientists at Norwegian Computing Center has contributed to the development of COHIBA: Petter Abrahamsen Pål Dahle Frode Georgsen Vera Louise Hauge Gudmund Hermansen Odd Kolbjørnsen Lars Bakke Krogvik Vegard Berg Kvernelv Inge Myrseth Audun Sektnan Arne Skorstad Harald Soleng Ariel Almendral Vazquez Maria Vigsnes Ingrid Aarnes The front page shows two fences along well paths on top of a faulted surface on the Valhall carbonate field in the North Sea. The illustration is made by Ingrid Aarnes. We thank Aker BP for permission to publish the illustration.