Datapages, Inc.Print this page

A Fully Integrated Approach for Fracture Characterization Using Geological and Reservoir Engineering Data: The Kuyumba Oil Field, Eastern Siberia Case History


Fonta, Olivier1, Luca Mattioni1, Sylvain Sarda1, Victor Ryabchenko2, Evgueni Sokolov3, Reval Mukhametzyanov4, Sergey Shlionkin5, Vladislav Zereninov5, Irina Bobb1  (1) Beicip-Franlab, Rueil Malmaison, France (2) Slavneft-Krasnoyarskneftegaz,Krasnoyarsk, Russia (3) Slavneft Moscow, Russia (4) Sibneft E/P, Moscow, Russia (5) Scientific-Analytical Center of Slavneft, Tver, Russia


Fractured reservoirs analysis necessitates identifying the main types of fractures, to pre­dict their occurrence in the reservoir and to determine the hydraulic properties of the differ­ent fractures sets. Here, we present an innovative and promising, multi-disciplinary integrat­ed approach that includes geology (BHI, cores, wireline logs) and reservoir engineering data (production data, PLT, welltest). We applied this methodology to the Kuyumba oil field of Eastern Siberia, a tight dolomite reservoir where porosity and permeability is mainly provid­ed by the fracture network. Two main scales of fractures were firstly identified and predict­ed from the BHI images: joints and large-scale fractures (faults and fracture swarms). Vsh content and mechanical beds thickness were found to be the two main geological factors controlling the fracture distribution. BHI acoustic images enabled to measure an S/T ratio (fracture spacing/bed thickness) for each fracture set and for different shalyness. A 3D sto­chastic fracture model was then generated incorporating the two scales of fractures and constrained by the reservoir shalyness and the S/T ratio. The calibration of the hydraulic properties of the fractures was achieved through the second innovative part of our own methodology: the simulation of a synthetic well test using the 3D fracture model and matched with the real data. This resulted in the calibration of the hydraulic fractures conduc­tivity for each fracture type. These values were combined with the 3D stochastic fracture model to produce 3D fracture properties models (porosity, permeability and block size) for the Kuyumba oil field.