Integrating well and seismic data for characterisation of shale plays

Abstract

Shale plays have revolutionised the oil and gas industry in North America and exploitation of these kinds of plays is steadily gathering pace in other parts of the world. Because hydrocarbon bearing shales usually have insufficient permeability to allow significant flow to a well, production from these unconventional reservoirs comes with unique challenges. Optimizing recoverable reserves from shales requires strategic placement of horizontal wells: placing the well in the best areas, drilling the lateral in the proper direction and keeping the lateral portion of the wellbore in the optimum layer. It further requires production stimulation by hydraulic fracturing (fracking) of the rocks to connect the natural fractures with induced near-well fractures. In this paper, we present a methodology to identify these optimum areas and layers in the shales using a seismic characterisation workflow where well and seismic data are rigorously integrated. The first part of the approach is well data analysis to extract petrophysical, rock physics and mechanical information. Shale formations have a complex mineralogy requiring a sophisticated petrophysical analysis. Then a seismic inversion is performed to predict rock properties, which characterise the shale reservoirs and importantly allow us to predict how the rocks will respond to fracking. The final part of the methodology is an interpretation of multiple rock property models in terms of defined shale facies. A Bayesian approach was adopted to generate shale facies models that describe the thickness and complex architecture of shale reservoirs. These facies models can be used to significantly reduce the risk of poorly performing wells and improve asset performance.