Nuclear-Magnetic-Resonance Petrophysics in Thin Sand/Shale Laminations

SPE Journal ◽  
2010 ◽  
Vol 16 (02) ◽  
pp. 223-238 ◽  
Author(s):  
Chanh Cao Minh ◽  
Padmanabhan Sundararaman

Summary We discuss the use of nuclear-magnetic-resonance (NMR) logging in the petrophysical evaluation of thin sand/shale laminations. NMR helps detect thin beds, determine fluid type, establish the hydrocarbon type and volume if hydrocarbon is present, and, finally, determine the permeability of the sand layers (as opposed to that of the sand/shale system). Experiments were conducted on samples of 100% sand, 100% clay, and sand/clay layers with an NMR-logging tool at surface to verify the characteristic T2 bimodal relaxation distribution often observed in NMR logs that are acquired in thin beds. From the bimodal distribution, it is often possible to determine a cutoff to separate the productive sand layers from the shale layers and, with it, the porosity fraction of each component. Subsequently, the sand fraction, or net/gross ratio, can be estimated assuming that the 100%-sand porosity is known. Because gas, oil, and water have different NMR properties, fluid-typing techniques such as 2D NMR offer useful insights into the fluid type and properties in thin-layer sands. Because the laminations thickness is often less than the antenna aperture, the estimated permeability of the sand/ shale system will undercall the true permeability of the sand layers only. In this case, their permeability can be estimated quickly from Darcy's fluid-flow model. We show examples of thin sand/shale laminations that are oil-bearing and gas-bearing. In each case, the NMR detection was verified against borehole-imaging logs, and the fluid type in the sands was determined from multidimensional NMR analysis. The derived hydrocarbon volume was then compared with the results estimated from a triaxial induction tool. Permeability of the sand layers was also computed and compared to that of nearby thick sands. Core data in one well was used to validate NMR detection, porosity, permeability, and net sand thickness.

2020 ◽  
Vol 8 (4) ◽  
pp. T823-T833
Author(s):  
Hai-Tao Li ◽  
Shao-Gui Deng

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.


2020 ◽  
Vol 17 (2) ◽  
pp. 185-196
Author(s):  
Shyamal K. Jash ◽  
Dilip Gorai ◽  
Lalan C. Mandal ◽  
Rajiv Roy

Flavonoids are considered as a significant class of compounds among the natural products, exhibiting a variety of structural skeletons as well as multidirectional biological potentials. In structural elucidations of natural products, Nuclear Magnetic Resonance (NMR) spectroscopy has been playing a vital role; the technique is one of the sharpest tools in the hands of natural products chemists. The present resume deals with hard-core applications of such spectral technique, particularly in structural elucidation of flavonoids; different NMR techniques including 1H-NMR, 13C-NMR, and 2D-NMR [viz. 1H-1H COSY, COLOC, HMBC, HMQC] are described in detail.


2015 ◽  
Vol 3 (1) ◽  
pp. SA77-SA89 ◽  
Author(s):  
John Doveton ◽  
Lynn Watney

The T2 relaxation times recorded by nuclear magnetic resonance (NMR) logging are measures of the ratio of the internal surface area to volume of the formation pore system. Although standard porosity logs are restricted to estimating the volume, the NMR log partitions the pore space as a spectrum of pore sizes. These logs have great potential to elucidate carbonate sequences, which can have single, double, or triple porosity systems and whose pores have a wide variety of sizes and shapes. Continuous coring and NMR logging was made of the Cambro-Ordovician Arbuckle saline aquifer in a proposed CO2 injection well in southern Kansas. The large data set gave a rare opportunity to compare the core textural descriptions to NMR T2 relaxation time signatures over an extensive interval. Geochemical logs provided useful elemental information to assess the potential role of paramagnetic components that affect surface relaxivity. Principal component analysis of the T2 relaxation time subdivided the spectrum into five distinctive pore-size classes. When the T2 distribution was allocated between grainstones, packstones, and mudstones, the interparticle porosity component of the spectrum takes a bimodal form that marks a distinction between grain-supported and mud-supported texture. This discrimination was also reflected by the computed gamma-ray log, which recorded contributions from potassium and thorium and therefore assessed clay content reflected by fast relaxation times. A megaporosity class was equated with T2 relaxation times summed from 1024 to 2048 ms bins, and the volumetric curve compared favorably with variation over a range of vug sizes observed in the core. The complementary link between grain textures and pore textures was fruitful in the development of geomodels that integrates geologic core observations with petrophysical log measurements.


2021 ◽  
Vol 21 (1) ◽  
pp. 438-449
Author(s):  
Weifeng Sun ◽  
Wei Ju ◽  
Yan Song ◽  
Yong Qin

The Lower Cretaceous Xiagou Formation is an important tight oil reservoir in the Qingxi Depression of the Jiuxi Basin. The micro-nanopore system within the reservoir requires a comprehensive analysis to improve the production of tight oil there. Nuclear magnetic resonance (NMR) experiments have been widely used for the petrophysical characterization of sandstones and carbonates. In the present study, the NMR experiment was applied to obtain the characteristics of the micro-nanopore system and permeability in the Lower Cretaceous Xiagou pelitic dolomite reservoir. According to the distribution shape of the transversal relaxation time (T2) obtained under the 100% water-saturated condition (Sw), the samples are divided into four groups: (i) group I, two obvious peaks (P1 and P2); (ii) group II, an obvious high peak of P1 at 0.1˜1.0 ms and a relatively low peak of P2; (iii) group III, an obvious high peak of P2 and a relatively low peak of P1; and (iv) group IV, three peaks. In general, the distribution shape of T2 under the initial condition (Sini) is unimodal, with all its peaks lower than those under the Sw condition. The NMR T2 spectrum reflects the distribution of the rock pore radius. Most of the pore radius distributions are bimodal, and the main pore radius ranges from 10 nm to 70 nm. Three patterns can be identified and determined based on the distribution of the pore radius: I—unimodal distribution, II—bimodal distribution and III—trimodal distribution. The results indicate that the porosity in the Xiagou reservoir ranges from 1.17% to 6.89%, with an average of 3.33%. The permeability ranges from 0.03×10−3 μm2 to 22.56×10−3 μm2, with an average of 2.95×10−3 μm2.


2015 ◽  
Vol 42 (2) ◽  
pp. 167-174 ◽  
Author(s):  
Ning LI ◽  
Kewen WANG ◽  
Gong ZHANG ◽  
Hongliang WU ◽  
Luzi ZHAO ◽  
...  

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