T-PROGS

Criterion

Explanation

General Description

The model provides reliable representations of subsurface heterogeneity. The purpose of T-PROGS is to enable implementation of a transition probability/Markov approach to geostatistical simulation of categorical variables. The overall goal of T-PROGS is to simplify conceptual aspects of geostatistical modeling yet maximize theoretical potential.

Model Domain

Subsurface modeling

Developer

Steven Carle, University of California, Davis

Hardware computing requirements

No specific requirements

Code language

Fortran

Original application

Public/proprietary and cost

T-PROGS (Transition Probability Geostatistical Software) version 2.1., was developed by the Department of Land, Air and Water Resources, University of California, Davis. There is no cost for the software.

Physically or empirically based

Physically based

Mathematical methods used

The model provides reliable representations of subsurface heterogeneity incorporating "soft" geologic information into Markov-chain models of spatial variability to produce geologically plausible realizations of subsurface heterogeneity. The hydrostratigraphy is characterized in a probabilistic manner by four geostatistical model parameters: (1) number of major textural categories (i.e. facies); (2) volume proportions of categories; (3) mean lengths (and thereby anisotropy ratio of mean length) of facies; and (4) juxtapositional tendencies (i.e. degree of entropy) among the facies. These parameters can be estimated either empirically through direct measurement (from well logs, drilling logs and soil survey maps) or through inference based on qualitative geologic interpretation (e.g. Carle, 1996; Weissmann et al., 1999).

Implementation of T-PROGS involves three main steps: (a) calculation of transition probability measurements, (b) modeling spatial variability with Markov chains, and (c) conditional simulation.

Input data requirements

The T-PROGS software is used to perform transition probability geostatistics on borehole data. Parameter files are prepared to administer input data for the executable codes. Two main data formats are used, one for point data and the other for gridded data. Point data, in particular coded lithologies located in a coordinate system or bivariate statistics computed as a function of lag (variograms, transition probabilities, etc.), are stored in a free-format ''GEOEAS'' ASCII format. Grid data, in particular 3-D Markov chain models and conditional simulations, are stored in a compact binary format. The simulations can also be output in an ASCII format to promote portability. The PS and EPS graphics files are also produced in ASCII format.

Outputs

T-PROGRS generates a 3-D realization, and the view of the realization. The output of the T-PROGS software is a set of N material sets on a 3D grid. Each of the material sets is conditioned to the borehole data and the materials proportions and transitions between the boreholes follows the trends observed in the borehole data.

Pre-processing and post-processing tools

N/A

Representation of uncertainty

Uncertainty is represented by varying the geostatistical model parameters.

Prevalence

Widely used to study heterogeneous aquifer systems.

Ease of use for public entities

Readily available to public entities.

Ease of obtaining information and availability of technical support

T-PROGS is included as utility for site characterization in the GMS software, with an available tutorial (https://www.aquaveo.com/software/gms-81tutorials). A manual is freely available online.

Source code availability

T-PROGS is available on request by e-mail to the author.

Status of model development

The spMC: Modelling Spatial Random Fields with Continuous Lag Markov Chains package extends the functionality of the T-PROGS software to R users.

Challenges for integration

The primary challenge for integration is availability of high-quality data (well and borehole logs) for model input. The software could be effectively used in the Delta to characterize the subsurface.