Michael Thambynayagam

Production Forecasting and Analysis for Unconventional Resources

Horizontal well drilling with multistage fracturing technology has been the common practice to develop unconventional resources. During the development of such resources, we are often faced with the following questions: How can we optimize the stimulation treatment? How much can the well produce? What are the production data telling us? Answering these questions requires technologies and tools to be able to forecast and analyze the production behavior of fractured wells. We investigate the physics and mathematics involved in production forecasts of both planar fractures and fracture networks that are generated due to stress isotropy and pre-existing natural fractures. We use analytical methods because they give rigorous yet very fast solutions. Since simulation expertise is not required to use our model, it is an accessible tool for multiple disciplines. A new nodal analysis approach is proposed for unconventional resources. Production forecasting enables the optimization of a well stimulation treatment, and helps to determine, for example, the number of fracture stages and the amount of proppant to use. Case studies illustrate the concept and some of the practical aspects of fractured well production, such as the impact of propped conductivity and unpropped conductivity. The composite workflow for diagnosis and analysis of production data specific to unconventional resources was applied to real case examples. The workflow involves flow regime identification, decline curve analysis, and rate transient analysis. The workflow is easily scaled from single-well level to well clusters to full field implementation.

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.