Time Domain Analysis Numerical Simulation and Influence Factors of NMR Logging

Time Domain Analysis (TDA) of NMR analyzer logging data has been successfully used to identify and evaluate quantitatively the oil and gas layers. The successfulness of TDA method, however, can be affected by the complex pore structure of rock and the changing properties of reservoir fluids. This paper uses numerical simulation to study the performance of TDA method in the identification and quantitative evaluation of fluids from different kinds of reservoirs.

A number of factors are analyzed, including the type of fluids, different pore sizes, signal-to-noise ratios (SNR) and NMR logging acquisition parameters. The results show that TDA method can accurately identify light oil layer (viscosity < 5mPa.s). In oil-bearing water layer with small-pore movable water, TDA method can accurately determine the oil porosity of formation; in oil-bearing water layer with big-pore movable water, however, TDA method could over-estimate the actual oil porosity of formation.

In a macroporous water layer, a short waiting time of 1s is not sufficient for the water to fully recover in the measurement; consequently, the presence of strong water signal in the differential spectrum of TDA could produce a result that is the opposite of the test result.

In gas layer, TDA method can accurately determine the gas porosity of formation. However, in gas-bearing water layer with small-pore movable water, benchtop NMR results are usually inconsistent with test results. Differential spectra of TDA between gas layer bearing water with big-pore movable water and small-pore oil gas layer can have similar features, which is often difficult to differentiate.

It is suggested to combine the dual-echo-spacing logging data to distinguish the gas layer bearing water with big-pore movable water. When the SNR is lower than a certain threshold, the right hand of the differential spectrum signal diverges, which reduces the accuracy in the determination of the hydrocarbon porosity of formation.

It is also found that high hydrogen index of gas is useful to distinguish the gas layer. A well-designed pre-logging plan can ensure that all logging parameters are optimized, which will improve the results of TDA method for the identification of hydrocarbon fluids.

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