Methodology to Integrate Multiscale Fracture Analyses in Fractured Systems Modeling: Application to Reservoirs of Southeastern Mexico
Naturally fractured reservoirs (NFR) are the main producers of hydrocarbon in the southeastern part of Mexico, and the need to be modeled is a challenge, since these models serve as guide for the locations of exploratory and development wells. The main objective of this work is to show a methodology to develop a 3D model that represents the orientation and distribution of conductive fractures in the reservoirs. This task requires analysis of fracture attributes and integration of data from different scales: thin sections, cores, images logs and seismic. We applied the SDPS (Structural-Diagenetic-Petrografic-Study) methodology to calibrate and to extrapolate the attributes of conductive aperture and fracture density. A 3D geological model, built from structural seismic interpretation and geomechanical data, was created to compute structural attributes. The final products were a Discrete Fracture Network that simulates each fracture set, and a flow model for each conductive set. Six wells, eleven cores, nineteen structurally oriented thin sections, six-hundred thin sections from cutting samples, five images logs, and one triaxial test from two oil and gas fields were analyzed. The two fields, located in the southeast of Mexico, consist of two main reservoirs: carbonate basinal facies, with less than 2% of matrix porosity, and an internal ramp facies with porosities of 4 to 6%. Based on their structural-diagenetic origin, five fractures sets were identified. Two are conductive: Set 4 (NE-SW) and Set 5 (N-S), and three sets are sealed: Set 1 (N-S), Set 2 (NW-SE), and Set 3 (E-W). The SDPS indicates that deformation degree, porosity and diagenetic processes (recrystallization) were the main geological controls of fracturing. Geomechanical data was used to analyze the deformation of the rock and to compute structural attributes which were integrated with the SDPS results to model the conductive sets and to predict their distribution. With the result of this modeling has been verified that the trajectory of the wells T-1, 3, 11, and 23 intercepted the main conductive fractures sets favorably, but it was not the case for T-12 and 1 DL wells. The well N-1 cut just a little favorably the main fracture sets. The wells productivity confirms the quality of fracture sets identified. Therefore, this work demonstrates that the results of this methodology can be used as a guide to propose new exploratory and development well locations.
AAPG Datapages/Search and Discovery Article #90189 © 2014 AAPG Annual Convention and Exhibition, Houston, Texas, USA, April 6–9, 2014