A partitioning interwell tracer test (PITT) is a method for estimating oil volume
and/or oil saturation in the swept zone between a set of injectors and producers in a
reservoir. One of the methods for analyzing PITTs is the method of moments, which is
based upon calculating the first temporal moment of the tracer concentrations in the
produced fluids. PITTs have many advantages over other methods for estimating oil
saturation by measuring over a much larger volume than a single well tracer test and a
well log. It is especially important to know the remaining oil saturation as accurately as
possible before applying enhanced oil recovery methods. PITTs also provide valuable
information on swept volumes between wells, flow paths, and breakthrough times. A
very general derivation of the method of moments applied to PITT data is presented in
this dissertation. This derivation shows that the method of moments can be used for
three-dimensional, heterogeneous reservoirs under very general conditions. The general
derivation and its verification with numerical simulations shows that the method is not
limited to residual oil saturation as generally assumed, but can be extended to mobile oil
saturation (or any multiphase flow problem). PITTs in naturally fractured reservoirs are an extreme example of heterogeneous reservoirs that can be analyzed by the method of
moments, although the time to conduct such tests can be generally very long. For this
reason, the concept of natural tracers was investigated and analyzed. The technique of
using natural tracers is based on the idea of measuring a naturally residing petroleum
organic component such as organic alcohols and acids. Since natural tracers originate in
the oil itself, its use can be less expensive and more environmentally friendly than the use
of injected chemical or radioactive tracers, and can take less time to produce a useful
signal. The synthetic tracer data in naturally fractured reservoirs as well as to singleporosity heterogeneous reservoirs are generated using numerical simulators. These data
were analyzed under a wide range of reservoir conditions using both the method of
moments and inverse modeling using a program developed at TAMU.Petroleum and Geosystems Engineerin
