Comparison between our predicted fracture model (in purple) and the fractures observed on borehole images (light blue disks) in a well from the Kraka field.

DHRTC Researchers Publish Book about Natural Fracture Networks

Wednesday 04 Nov 20

A new book release presents the results from years of simulation research at DHRTC, where researchers have developed and tested new methods for predicting the occurrence of natural fractures in subsurface reservoirs. The authors behind the book are Senior Researchers Michael Welch and Mikael Lüthje, and Postdoc researcher Simon Oldfield.

The Making of the Book

“The idea for the book came out of a desire to publish and publicise our work, both for other researchers and for those in the industry who may find it useful. However, there are many different aspects to the method, describing nucleation and propagation rates for different fracture types, interactions between growing fractures, and the effect of the fractures on the stress and strain in the rock”, the authors state.

“We also wanted to describe some of the interesting results and applications of the fracture models. There was too much to fit into one journal paper, but we wanted to keep everything together to provide a comprehensive reference, so we decided on a book format.”

The Importance of Natural Fractures

Natural fractures are important, especially in low permeability reservoirs such as the chalk reservoirs of the Danish North Sea, as they act as major flow pathways, controlling the flow of fluid around the reservoirs. They must therefore be taken into account when modelling the flow of fluids through the subsurface, whether hydrocarbons, water or CO2.

However, it is impossible to image them directly in the subsurface. They are too small to be seen by geophysical imaging methods such as seismic data. While they can be seen in wells, these only give limited coverage as there may be only a few wells in a field many kilometres in size, and they do not give any information about the size of the fractures or how well connected they are. Both are important factors controlling fluid flow through the fractures.

The authors have therefore developed a method for modelling fractures in the subsurface by simulating the growth of the fracture network, based on fundamental geomechanical principles and knowledge of the geological history of the reservoir. This method has been tested against both outcrops and subsurface reservoirs and shown to give accurate and useful results.

Book Overview

The book starts with a review of previous work in fracture modelling and presents a conceptual model for the growth of a natural fracture network in a reservoir layer. It then describes in detail how to derive mathematical equations for the density, distribution, size, connectivity and anisotropy of the natural fractures, based on the geological evolution of the reservoir. These equations are then used to investigate how the evolution of the fracture network controls the fracture geometry – the authors show, for example, how the fracture length can be controlled by the rate of fracture nucleation and propagation, and how a fracture network that grows quickly will tend to be more anisotropic than a fracture network that grows slowly. It is also shown that the method can predict various aspects of the fracture geometry observed in three fractured outcrops, before finally demonstrating the application of the method on two subsurface examples: an oilfield in the Danish North Sea and an onshore geothermal prospect in the Netherlands.

This book will be of interest to anyone curious about understanding and predicting the evolution of complex natural fracture networks across large geological structures. It will be helpful to those modelling fluid flow through fractures, or the geomechanical impact of fracture networks, in the hydrocarbon, geothermal, CO2 sequestration, groundwater, and engineering industries. You can buy the book titled Modelling the Evolution of Natural Fracture Networks: Methods for Simulating the Nucleation, Propagation and Interaction of Layer-Bound Fractures on Amazon or Springer. Besides the authors, the fracture prediction group in DHRTC also include postdoc researcher Michael Sargado. 

Image: Comparison between our predicted fracture model (in purple) and the fractures observed on borehole images (light blue disks) in a well from the Kraka field. ©2020 The authors.