Improved Welltest Analysis in Heavy Oil Reservoirs Using Fluid and Heat Flow Models

Heavy oil reservoirs account for a large proportion of remaining oil reserves. These reservoirs are typically different from conventional oil reservoirs in many ways. Most heavy oil reservoirs are shallow reservoirs lying about 1000m or less below the surface (Awotunde and Azad 2014; Santos et al. 2014). This makes the pressures in such reservoirs relatively low (about 300-500psi), and the porosity and permeability of such reservoirs quite high (permeability often greater than 1000mD and porosity often ranges from 0.2 to 0.35) (Awotunde and Azad 2014; Santos et al. 2014). Also, due to the very high viscosity of the fluid at discovery (typically in the range of 100cp-100,000cp at initial reservoir conditions), some of these reservoir oils would not flow unless some heat is supplied to mobilize them. Furthermore, heavy oils are usually denser than conventional oils (light and medium oils)) and based on the American Petroleum Institute (API), oils having an API index of 20oAPI or less are classified as heavy (Santos et al. 2014; Batzle et al. 2006; Ramos-Pallares 2017). Thus, a proper management of these heavy oil resources requires efficient and meaningful characterization of the reservoir, the fluid and the flow behavior of the heavy oil. Reservoir characterization typically involves the determination of reservoir and boundary types, and the estimation of reservoir properties such as permeability, near-wellbore damage effect, thickness, and external radius. In cases in which the properties of heavy oil and its ability to flow is significantly influenced by temperature gradients, it becomes necessary to estimate the thermal properties of the heavy oil that influence its flow characteristics. The objective of the work is to solve the fluid flow model (diffusivity equation) and heat transport model (advection-diffusion equation) to obtain pressure and temperature as functions of time at the wellbore and at some equaivalent distance in the reservoir. The pressure and temperature obtained at ever time interval are used to update the reservoir and fluid properties and the updated properties are used in subsequent computations of pressure and temperature. This sequence of updating the reservoir and fluid properties lead to improved estimates of pressure and temperature profiles. The pressure obtained from this will be matched to pressure data measured from the wells to obtain welltest parameters as as permeability, skin factor, wellbore storage coefficient, reservoir size, etc. Results from this work would then be compared with those from traditional welltest methods that do not consider variation of fluid and reservoir properties with temperature.