Study on Nuclear Magnetic Resonance Logging T2 Spectrum Shape Correction of Sandstone Reservoirs in Oil-Based Mud Wells

The oil-based mud filtrate will invade the formation under the overbalanced pressure during drilling operations. As a result, alterations will occur to the nuclear magnetic resonance (NMR) response characteristics of the original formation, causing the relaxation time of the NMR T2 spectrum of the free fluid part to move towards a slower relaxation time. Consequently, the subsequent interpretation and petrophysical evaluation will be heavily impacted. Therefore, the actual measured T2 spectrum needs to be corrected for invasion. For this reason, considering the low-porosity and low-permeability of sandstone gas formations in the East China Sea as the research object, a new method to correct the incorrect shape of the NMR logging T2 spectrum was proposed in three main steps. First, the differences in the morphology of the NMR logging T2 spectrum between oil-based mud wells and water-based mud wells in adjacent wells were analyzed based on the NMR relaxation mechanism. Second, rocks were divided into four categories according to the pore structure, and the NMR logging T2 spectrum was extracted using the multidimensional matrix method to establish the T2 spectrum of water-based mud wells and oil-based mud wells. Finally, the correctness of the method was verified by two T2 spectrum correction examples of oil-based mud wells in the study area. The results show that the corrected NMR T2 spectrum eliminates the influence of oil-based mud filtrate and improves the accuracy of NMR logging for calculating permeability.

Eliminating Diffusion Effects from NMR Logging Data for Enhanced Carbonate Pore Typing

Transverse relaxation (T2) times measured by multi-frequency, multi-gradient nuclear magnetic resonance (NMR) logging tools are affected by diffusion-induced enhanced relaxation which reduces the sensitivity to pore size in slow-relaxing formations such as macroporous carbonates and complicates the integration with zero-gradient core NMR data. We propose a solution for eliminating the diffusion-related uncertainties using intrinsic T2 distributions, obtained by a new inversion-forward modeling-inversion (IFMI) method, for carbonate pore typing applications. The NMR logs presented in this paper are based on data measured at five frequencies where the static magnetic field gradient varies from 26 to 55 G/cm. The high-quality echo signals are processed using a three-step IFMI differential signal analysis approach which nullifies diffusion effects due to the tool gradient and the potentially present internal gradient caused by paramagnetic minerals in the formation. The resulting diffusion-free intrinsic T2 distribution accentuates fine pore size variations and allows better discernment of micro-, meso-, and macropore systems of complex carbonate reservoirs. Multi-frequency NMR data, acquired in multiple wells, were processed and analyzed in several ways. First, apparent T2 distributions were obtained separately for individual frequencies. Discrepancies between the results of different frequencies clearly indicated that in macro- and mesoporous carbonates the diffusion effect is significant even with TE=0.3ms. This leads a peak broadening observed in the apparent T2 spectrum from conventional NMR processing, where echo trains from different frequencies are averaged in time-domain prior to the inversion. With the IFMI processing, individual-frequency echo trains are first pre-processed using a 2D NMR inversion whose results are used to forward model a diffusion-free echo train without prior assumptions on reservoir fluid diffusivity D. A second inversion, applied on the diffusion-free echo train, yields the intrinsic T2 distribution. The intrinsic T2 distribution has a noticeably higher spectral resolution in carbonate formations where diffusion effect is significant. The intrinsic T2 logs are expected to be more consistent with other gradient-free NMR measurements such as core NMR or LWD NMR data sets.

Application of nuclear magnetic resonance logging in the low-resistivity reservoir — Taking the XP area as an example

With the deepening of exploration and development, many low-resistivity reservoirs have been found in the XP area. We have found that the genesis of these low-resistivity reservoirs is that they contain a lot of very fine sand, which leads to the high content of bound water in the reservoirs and reduces resistivity. Compared with normal oil reservoirs, these reservoirs show low resistivity and high natural gamma, which makes it difficult to identify reservoirs qualitatively and calculate parameters quantitatively. Using conventional logging interpretation methods, the wrong shale content and porosity will be obtained, and such reservoirs may even be judged as mudstones. To solve this problem, we extract a characteristic parameter from the T2 spectrum of nuclear magnetic resonance (NMR) logging, which can effectively identify such reservoirs. In addition, we have innovatively adopted an optimized logging interpretation method for integrated NMR logging and conventional logging, which has effectively improved the parameter calculation accuracy of this type of reservoir and achieved a good application effect in the XP area.

A fast inversion method of 2D nuclear magnetic resonance based on the novel hybrid algorithm

To make up for the limitations and improve the accuracy of 1D nuclear-magnetic-resonance (NMR) logging in the evaluation of formation fluid properties, 2D NMR logging has become the focus of research. Increasing the sequence and inversion parameters of the 2D NMR can effectively improve the antinoise properties and resolution of the inversion, but at the same time, the reduced inversion speed and increased memory occupied will put forward higher requirements on the computer configuration and add to the cost of calculation, which poses challenges to the application of the traditional 2D NMR inversion algorithms. In view of the above defects, we have developed a new fast 2D NMR inversion LSQR-RSVD hybrid algorithm, and we have used the nonnegative least-squares (LSQR) calculation result as the initial value of the RSVD inversion. Taking oil-water and gas-water models as examples, the 2D NMR inversion effects of ( T2, D), ( T1, T2) are analyzed in detail, and ( T1, D) is also discussed by several groups of echo trains with variable echo interval ( TE) and waiting time ( TW). Compared to the inversion algorithm commonly used, the new hybrid algorithm can improve the inversion speed and significantly reduce the memory occupancy. Its remarkable advantages can further promote the application of 2D and even multidimensional NMR logging in practice.