Peter Gerhard Tilke

Automated Field Development Planning for Unconventional Shale Gas or Oil

We present a framework that automatically generates an optimal well placement plan (WPP) based on a reservoir model of a shale gas field. The proposed WPP comprises wells, surface locations such as pads, well completion locations, and the drilling schedule. A suite of high-speed computational components allows generating this WPP in minutes. Different development strategies can be rapidly investigated. The WPP is optimized using a constrained downhill-simplex approach. During a trial, WPPs proposed by the optimizer in previous trials were extrapolated to propose a new WPP. The proposed WPP must satisfy a wide range of geometric, operational, contractual, and legal constraints on the surface as well as in the overburden and reservoir. When a feasible WPP is discovered during a trial, the production forecast is computed using a high-speed semianalytic reservoir simulator. The framework supports a variety of objective functions, including recovery, net present value, return on investment, and profitability index. Optimization in the presence of subsurface uncertainty considers an ensemble of reservoir models. A proposed WPP will then have an uncertainty in the forecast value. For a specified aversion to risk, a conservative or aggressive WPP can then be optimized.

The Heterogeneity Spectrum: A Method for Quantifying the Extent of Spatial Heterogeneity as a Function of Length Scale in Complex Materials

Imaging measurements represent a powerful means of characterizing materials with complex spatial structure, such as naturally occurring porous media. In this contribution we present the application of the heterogeneity spectrum, which is a newly developed method for quantitative analysis of imaging data. The heterogeneity spectrum transforms imaging data into a measurement of the extent of spatial heterogeneity as a function of length scale. The inversion rigorously considers the support of the experiment, and the length scales of heterogeneity to which a measurement is sensitive are determined from the experimental voxel size and sample size. Heterogeneity spectra are shown for magnetic resonance imaging and thin section imaging data from several complex carbonate rock core samples. These measurements are sensitive to heterogeneity at length scales ranging many orders of magnitude and are shown to provide a useful characterization of these porous media.