Water saturation modeling using modified J-function constrained by rock typing method in bioclastic limestone

Abstract

Combining both geological and petrophysical properties, a reliable rock typing scheme can be achieved. Two steps are included in rock typing. Step 1: rocks are classified into lithofacies based on core observations and thin sections; Step 2: lithofacies are further subdivided into rock types according to petrophysical properties such as MICP (Mercury Injection Capillary Pressure) and K-Phi relationships. By correlating rock types to electrofacies (clusters of log data), we can group the target formation into 12 rock types. Then it is possible to predict the distributions of rock types laterally and vertically using wireline logs. To avoid the defect of the classical J-function saturation model that includes permeability which is quite uncertain especially in carbonate rocks, a modified J-function was created and used in the paper. In this function, water saturation is simply expressed as a function of height above free water level for a specific rock type. Different water saturation models are established for different rock types. Finally, the water saturation model has been successfully constructed and verified to be appropriate.

A Novel Energy Lifting Approach Using J-Function and Flow Zone Indicator for Oil Fields

“…As capillary pressure depends on pore size radius, Leverett J-function can also be used to determine pore sizes for rocks of uniform properties. In complex reservoirs, as the water saturation is a function of capillary pressure height and rock properties, Leverett J-function, J(S w ) works much better than normal P c (S w ) [23,24,34,[36][37][38]. This research is useful in reducing the simulation complexity as well as the uncertainty associated with reservoir modelling.…”

Well log data super-resolution based on locally linear embedding

“…Therefore, in order to enhance the production capacity of the unconventional remaining oil and gas resources, the reservoir modelling resolution should be as high as possible. Meanwhile, the high-resolution logging curves can better provide the possibility to predict the location of lost circulation [2], lithology identifies [3], and predict the productivity of heterogeneous reservoirs [4,5]. In practice, because the vertical resolution of seismic data is too low and the cost of acquisition of core and other high resolution logging data is too high, it is an inevitable choice to employ conventional well log data to enhance the vertical resolution of the final reservoir models.…”