3.1 Task 1.1: Collection of Fractured Reservoir Site Characterization Data
3.2 Task 1.2: 3D Hierarchical Fracture Model
3.3 Task 1.3: Reservoir Compartmentalization
3.4 Task 2.1: Fracture Data Analysis Technology
3.5 Task 3.1: Linkage to Reservoir Models
3.6 Task 3.2: Integrated Fractured Reservoir Discrete Fracture Model
3.7 Task 4.1: Reservoir Performance Data Collection
3.8 Task 4.2: Simulation of Fractured Reservoir Production
3.9 Task 4.3: Technology Evaluation
3.10 Task 5.1: Electronic Technology Distribution
3.11 Task 5.2: Presentations
3.12 Task 5.3: Workshop
The project web site is one of the few in the world which provides web access to high-quality reservoir site characterization data. This data is useful to oil companies evaluating comparable reservoirs, and to researchers studying reservoir characterization. Organizations which have downloaded data from the site characterization database are listed in Table 4-2.
Fracture systems in the geologic environment consist of multiple sets of discontinuities that often interconnect to create conditions for mechanical failure and flow. A comprehensive study of natural fracture systems resulted in classification of five major fracture-producing geologic settings: folds, crustal faults, crustal extension, thermal contraction, and central intrusive and extrusive structures. The geometries of the fracture systems in different geologic settings, determined by the geologic sequence of fracture formation, rock lithology, and regional and local principal stress directions, can be described in terms of fracture intensity, orientation, and region of existence.
Since the field sampling methods are essentially 1D (logs and cores) and 2D (outcrop maps), there is usually great uncertainty about the actual 3D geometry and connectivity of natural rock fracture systems. To reduce that uncertainty, the 3D Hierarchical Fracture Model (HFM) incorporates the geology into the inference procedure. The model reproduces rock fracture systems through superposition of hierarchical fractures sets, using three stochastic processes that reflect inherent relationships between the fracture system geometry and the underlying mechanics. The model uses Poisson plane process, Poisson line tessellation, and random 3D rotation and translation, to represent orientations of potential fracture planes, fracture intensity, and relationships to local geologic structures. The 3D fracture system model was implemented in the computer program GeoFrac, written in C/C++ for Unix.
The geologic and numerical model was applied in a case study of the fracture system in Permian sedimentary rocks in West Texas. The study included development of a conceptual model for the geologic evolution of the fracture system in the reservoir formations of the Yates oil field. Numerical simulations involved generation of fracture sets related to the regional stresses and depositional trends, and to the asymmetric anticlinal structure of reservoir strata. Comparison of the numerically generated fracture system to field data showed a good match by dip, strike, and spacing of fractures intersected by boreholes.
In a fractured reservoir, a well produces from the fracture network intersecting the well, and from the matrix that feeds into the fracture system. Many, if not most, fractured reservoirs contain fracture networks that are compartmentalized to some extent. This compartmentalization is due to both the geometry of the fractures, and to the fluid flow properties of individual fractures. As a result, production from a well or zone in a well is limited to the fracture network(s) to which it is connected, and to the matrix that can feed into the fracture system by means of pressure-depletion or gravity drainage.
In this task, the project team developed quantitative measures of reservoir compartmentalization in terms of parameters which can be readily applied to reservoir engineering. The measures developed address:
These quantitative measures of reservoir compartmentalization have the potential to provide significant improvements to fractured reservoir production. For example, estimating the horizontal cross-section of reservoir compartments is useful for
The compartmentalization technologies were implemented as a Windows 95/NT software package, "FraCluster", which is distributed through the project web site.
Research was carried out to develop advanced technologies for analysis of fractured reservoir data in support of the use of discrete feature network (DFN) approaches for reservoir engineering. Four technologies were developed:
For discrete feature network models to be a practical tool for reservoir simulation, they must be directly linked to commonly used reservoir stratigraphic models such as GeoFrame, IRAP, GoCAD, and StrataModel. Stratigraphic models use a cell-based approach to define a geographic database of information on reservoir properties, stratigraphy and structure. Faults are often used as boundaries for groups of cells, or as control surfaces for interpolating stratigraphy and lithology. Both large displacement faults and smaller displacement faults can compartmentalize reservoir units There faults influence sweep efficiency, production rates and ultimate recovery.
In this task, the project team developed an approach to link stratigraphic models to discrete feature network models. The prototype "StrataFrac" has two functions:
This task includes the implementation of Task 2.1 technologies within a MS-Window 95/NT software framework, and development of technologies for discrete fracture analysis of the TAGS process.
The status of data analysis software development is described in Table 3-1. The theory, user instructions, and verification cases for this software is described in the project report, "Fracture Data Analysis Technologies," which is also available through the project web site.
Table 3-1 MS Windows 95 Analysis System
Software |
Application |
March 1998 Status |
| NeurISIS _1.0 | Orientation and Set Analysis | Available through Web Site. |
| FracDim _1.0 | Flow Dimension from Well Tests | Available through Web Site |
| Flare _1.0: | Flow Dimension from Discrete Fracture Networks | Available through Web Site |
| Spatial _1.0: | Spatial Data Analysis | Available through Web Site |
The technologies developed to link the conventional dual porosity (DP) approach to the DFN approach for modeling the TAGS improved oil recovery process will allow the DP approach to take advantage of some of the features of the DFN approach, without requiring reservoir engineers to be extensively retrained. It also allows the analyst to maintain many of the advantages of DP simulators such as ECLipse, including:
Approaches were developed and documented to derive the following DP model parameters from DFN models:
The project has collected and posted to the project web site over 30 megabytes of information concerning reservoir performance, fracture images, and well testing at the project study sites. This data is among the most actively accessed data on the project web sites, representing over 150 total data downloads.
In this task, reservoir simulations are being carried out to demonstrate the practical application of the technologies developed during the project. The results of these simulations, and the application of these results to completion and EOR activities will provide the basis for economic analysis of the value of the DFN approach at the project study site.
Future development of the Yates Field calls for a lowering of the fluid contacts and a thinning of the oil column. Even though fractures might form geometric pathways that encompass both the oil and the gas columns, only those pathways entirely within the oil column can contribute oil by means of the gravity drainage mechanism to a producing well. Thus, understanding tributary drainage volume and compartmentalization as a function of oil column thickness is important for optimizing deeper recompletions of existing wells and estimating when the oil column reaches a minimum produceable thickness.
To date, analyses have been carried out as part of the following reservoir simulations:
At the conclusion of the project, the technologies developed will be evaluated quantitatively to determine the benefit of the DFN approach and the TAGS process developed within this project. This analysis will include an assessment of the additional costs associates with DFN data collection and data analysis, and an estimation of the difference in recovery which occurred and are expected to occur from the use of DFN approaches and TAGS.
The project web site has been in operation since May, 1996. Golder Associates has maintained and updated the web site to provide distribution for:
For information on the activity at the project web site, please see Section 4.3 below.
Information on presentations made as part of the project is provided in Section 4.2 below.
At the conclusion of the project, a technology transfer workshop will be held to train engineers for the oil industry in the use of project-developed technologies. Planning for this workshop has already been initiated. Approximately 25-50 individuals are expected to attend.
