A New Practical Approach to Building a 3D Naturally Fractured Reservoir Model
Authors: Li D. , Liu J. , Sanchez-Barajas J. , Seader R. , Lanz-Torres C.L. 
Published: December 2007

A New Practical Approach to Building a 3D Naturally Fractured Reservoir Model D. Li, SPE, Western Atlas E & P Services*, J. Liu, SPE, Western Atlas E & P Services, J. Sanchez-Barajas, Pemex, R. Seader, SPE, Western Atlas E & P Services, and C.L. Lanz-Torres, Pemex

The nature of available data sources for reservoir characterization and simulation can be characterized as that most of geological and engineering data are generally available only in a single spatial direction or at some scattered blocks. Some of these data are defined at multiple spatial scales while others are defined at a single scale, and some of these data are available at dissimilar spatial scales. Systematic data integration techniques are needed for handling of the complicated nature of different data sources for 3D reservoir modeling.

This paper presents a new practical approach to building a complicated 3D naturally fractured reservoir model using all available data sources: seismic, log, core, lithology, well testing, and production. Unlike most of the recent data integration techniques, the new approach integrates different data sources by emphasizing the importance of the wide spread spatial scales on which data sources are defined. The criterion used in the paper is that data integration must be carried out at the same or similar scales. The basic tools used for data integration are scale-up and scale-down techniques. The modeling procedure includes both reservoir geometry modeling (e.g. structures, faults, and layers) and reservoir property modeling (e.g. porosity, permeability, and saturations etc.). The approach is applicable not only for naturally fractured reservoirs but also for non fractured reservoirs.

Introduction

Building a 3D naturally fractured reservoir model is critical to optimizing oil production and recovery efficiency for a naturally fractured reservoir. Most conventional logs and geologic tools lack capability to locate fractures that are critical for oil and gas production. Fractures can be anywhere and in any orientation without following their geologic/stratigraphic sequence. Recent developments in image logs now provide the capability to directly measure fracture density and orientation. But the industry is still facing problems, for example, that image logs are available at best on only a few wells in a field and that most fractured reservoirs still have no image logs. Therefore, the industry needs a technique that can efficiently extract fracture information from available data.

The following paragraphs present a new practical approach for extracting fracture information to build a reliable 3D reservoir model. The technique relies on a powerful tool, scaling up and down, by which different sources of data collected through seismic, log, core, well test, and production can be correctly handled. Based on scaling analysis, the chance to extract fracture information from existing data is very high.

Methodology

The technique starts with pressure transient test (PTA) data that are directly related to reservoir flow capacity, i.e. fracture permeability. Not all wells have PTA data, but all wells have production data. Individual well production plateau rates were found to best correlate with PTA kh (fracture permeability times thickness). Based on the correlation between production plateau and PTA kIlt, production kh (equal to PTA kh for PTA wells and calculated for non PTA wells) can be estimated. Production kh provides fracture information averaged in a large volume (scale), while logs provide fracture information averaged in a small volume (scale). Fracture information within well logs is very difficult to be identified by traditional petrophysical analysis. A single log contains insufficient fracture information, however a combination of many logs may reveal some fracture information. This study shows that mudcake log, lithology log, total porosity log, secondary porosity index log, and water saturation log etc. are good candidates for fracture identification. P. 293^