LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

An improved geomechanical model for the prediction of fracture generation and distribution in brittle reservoirs

Photo from wikipedia

It is generally difficult to predict fractures of low-permeability reservoirs under high confining pressures by data statistical method and simplified strain energy density method. In order to establish a series… Click to show full abstract

It is generally difficult to predict fractures of low-permeability reservoirs under high confining pressures by data statistical method and simplified strain energy density method. In order to establish a series of geomechanical models for the prediction of multi-scale fractures in brittle tight sandstones, firstly, through a series of rock mechanics experiments and CT scanning, we determined 0.85 σc as the key thresholds for mass release of elastic strain energy and bursting of micro-fractures. A correlation between fracture volume density and strain energy density under uniaxial stress state was developed based on the Theory of Geomechanics. Then using the combined Mohr-Coulomb criterion and Griffith’s criterion and considering the effect of filling degree in fractures, we continued to modify and deduce the mechanical models of fracture parameters under complex stress states. Finally, all the geomechanical equations were loaded into the finite element (FE) platform to quantitatively simulate the present-day 3-D distributions of fracture density, aperture, porosity, permeability and occurrence based on paleostructure restoration of the Keshen anticline. Its predictions agreed well with in-situ core observations and formation micro-imaging (FMI) interpretations. The prediction results of permeability were basically consistent with the unobstructed flow distributions before and after the reservoir reformation.

Keywords: fracture; geomechanical model; strain energy; improved geomechanical; density; prediction

Journal Title: PLoS ONE
Year Published: 2018

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.