Nuclear Magnetic Resonance Logging Research Articles

Predicting the impact of hydrocarbon saturation on T2 distribution curve of NMR logs – A case study

The Nuclear Magnetic Resonance (NMR) is a valuable technique that provides estimates of various rock and fluid properties, including porosity, permeability, and pore size distribution. The decay or relaxation time of NMR signals is directly related to the pore size, but altering fluid in the pore spaces would also change the T 2 distribution curve. This change is due to the different relaxation time of hydrocarbon and water. This study focuses on predicting NMR T 2 distribution curves at different water saturations using a single T 2 saturation at any given water saturation. To do so, NMR measurements were performed on 9 plugs each at different saturations. Two general equations were derived. The first equation is related to the water response, while the second equation is related to the oil response. These two equations were calibrated and verified using core data. The coefficient of determination (R 2 ) for the first equation is equal to 0.592, while it is equal to 0.975 for the second equation. T 2 distribution curves depend on the amount and the distribution of the fluids within the pore structure. The findings of this study can help to increase the accuracy of the petrophysical properties derived by NMR logging. • A new model is proposed to predict NMR's T2 distribution curve in the oil bearing rocks. • NMR measurements were investigated in 9 plugs individually in different saturations in an oil field. • Two general equations were derived. To validate the equations, five T2 distribution curves which are equivalent to the T2 distribution curve of 100% water saturated rock were constructed by using 5 experimental T2 distributions.

Evaluating the potential of carbonate sub-facies classification using NMR longitudinal over transverse relaxation time ratio

While the well log-based lithology classification has been extensively utilized in reservoir characterization, the classification of carbonate sub-facies remains challenging due to the subtle nuances in conventional well-logs. The nuclear magnetic resonance (NMR) log provides extra information of pore size and pore geometry features, improving differentiating carbonate sub-facies. Here we explore the feasibility of using the ratio between NMR longitudinal relaxation time and transverse relaxation time as a potential lithology indicator to determine carbonate sub-facies. We analyzed a series of logging data and corresponding core samples of Arbuckle Group carbonate containing mudstone, packstone, grainstone, incipient breccia, and breccia in northern Kansas for the characteristics of longitudinal relaxation times, transverse relaxation times, and longitudinal over transverse relaxation time ratios. The results show that mudstone, packstone, and grainstone exhibit high, intermediate, and low longitudinal over transverse relaxation time ratios, respectively, while incipient breccia and breccia have a wide range of longitudinal over transverse relaxation time ratios. Furthermore, we evaluated the potential of using longitudinal over transverse relaxation time ratios to classify carbonate sub-facies using multivariate analysis. By adding longitudinal over transverse relaxation time ratios to neutron porosity, total gamma-ray, and conductivity logs as inputs of automated facies classification, the prediction error decreased, especially for incipient breccia. On the contrary, when photoelectric log and computed gamma-ray are also available, adding longitudinal over transverse relaxation time ratios does not improve the accuracy of sub-facies classification. Our results suggest that longitudinal over transverse relaxation time ratio is an independent lithology indicator. However, it cannot replace other logs like gamma-ray and photoelectric logs in classifying carbonate sub-facies. Our study provided valuable evidence and credible elucidation of the importance and physicochemical mechanism of longitudinal over transverse relaxation time ratios, which is essential for deciphering NMR logging data in carbonate reservoirs. Cited as : Zhang, F., Zhang, C. Evaluating the potential of carbonate sub-facies classification using NMR longitudinal over transverse relaxation time ratio. Advances in Geo-Energy Research, 2021, 5(1): 87-103, doi: 10.46690/ager.2021.01.09

A method to predict heterogeneous glutenite reservoir permeability from nuclear magnetic resonance (NMR) logging

Permeability is an important input parameter in evaluating formation validity and predicting deliverability; its value is always estimated from porosity or other formation parameters based on the statistical methods. However, glutenite reservoir permeability prediction faces a great challenge due to the strong heterogeneity. In this study, to establish a reasonable model to predict heterogeneous glutenite reservoir permeability, 483 core samples were recovered from the Permian Jiamuhe Formation, Shawan Depression, northwestern Junggar Basin, China for routine physical property experiments; 21 of them were chosen to apply for laboratory nuclear magnetic resonance (NMR) measurements. After introducing the hydraulic flow unit (HFU) theory, these 483 core samples are classified into eight categories based on the flow zone indicator (FZI) difference, and applicative relationships of core-derived porosity and permeability are respectively established for every type of core sample. Meanwhile, based on the deeply analyzing of the expression of FZI and the classic Timur-Coates permeability-based model, a theoretical model of calculating FZI from NMR data is proposed. The involved input parameters are calibrated by using the experimental data of 21 core samples. After the established models are extended into field applications, the consecutive FZI curve is estimated from NMR logging to classify formations, and the corresponding relationships are used to predict permeability. Comparisons of the predicted FZI and permeability with core-derived results verify the reliability of the proposed models. They can be well used to precisely predict permeability in our target heterogeneous glutenite reservoirs.

Multi-parameter logging evaluation of tight sandstone reservoir based on petrophysical experiment

Acoustic, resistivity and nuclear magnetic resonance (NMR) logging are important means of reservoir evaluation. In this paper, the information of pore structure, such as the aspect ratio and the shape, is obtained by rock physical experiments like constant velocity mercury injection and casting thin section. Taking pore structure information as a link, the theoretical relations among acoustic-NMR, acoustic-resistivity and resistivity-NMR of rocks are studied, respectively, based on the differential equivalent model and fractal theory, and the theoretical derivation results are verified by AE acoustic emission experiment, rock resistivity experiment and NMR experiment. It is found that there is a power function relationship between the P/S wave velocity and the geometric mean value of NMR T2. Moreover, there are also power function relationships between the slowness of P/S wave and resistivity, and between the value of NMR T2 and the increase rate of resistance. Based on the above relationship, the gas reservoir can be identified by acoustic-resistivity-NMR multi-parameters in well G of the study area. Compared with the conventional P/S velocity ratio and P-wave slowness intersection method, the separation effect of gas and water is more obvious.

Formation Evaluation With NMR, Resistivity, and Pressure Data: A Case Study of a Carbonate Oil Field Off shore West Africa

In this paper, we examine fluids interpretation techniques in a prolific oil field in offshore West Africa. A sourceless logging program, consisting of logging-while-drilling (LWD) nuclear magnetic resonance (NMR), resistivity, and formation tester, was chosen to log the reservoir section in 6.5-in. holes. The purpose of this study is to answer questions related to asset appraisal and development with these limited measurements. Core data available are porosity, permeability, water salinity, Archie m and n, and Dean-Stark Sw. A comparison of the core and NMR log indicates that NMR total porosity is not affected by hydrocarbon in the pore space. We use a statistical method called factor analysis to deconvolve independent fluid modes from the T2 distribution and pick the T2 cutoff. The NMR irreducible water saturation (Swirr) computed with this cutoff agrees with Dean-Stark Sw. Continuous Sw is calculated with Archie’s equation with lab-measured parameters and validated against Dean-Stark Sw above the transition zone. The Timur-Coates model is used to estimate matrix permeability. The first application of this interpretation workflow is to confirm the free-water level (FWL) derived from pressure gradients. We found the Sw profile largely controlled by heterogeneity in rock textures. The presence of both good and poor-quality rocks makes log-based FWL picking difficult. We use Swirr from NMR to indicate rock quality and simplify our final interpretation. The FWL found by sourceless log interpretation is consistent with the initial FWL found by pressure gradients. The second application is perforation design. Zones with good porosity and low mobile water volume are selected for perforation, and a safe distance is maintained from FWL. As a result, all producer wells exhibit zero water cut.

A Design Scheme of Receiving System of Small-Diameter Nuclear Magnetic Resonance Logging Tool

Obtaining the information of shallow surface hydrogeological parameters is of great significance to the study of the groundwater cycle, the development and utilization of groundwater, and the protection of groundwater. Nuclear magnetic resonance (NMR) technology is the only method among all geophysical methods that can directly qualitatively and quantitatively measure groundwater content and evaluate aquifer reservoirs. The emergence of small-diameter NMR logging tools provides a powerful tool for the evaluation of shallow surface hydrogeological parameters. However, the low signal-to-noise ratio (SNR) of the NMR signal is still an important factor restricting the development of such instruments. In this article, we propose a design scheme for the receiving system of a small-diameter NMR logging tool. Its main design purpose is to improve the SNR of the receiving signal. The receiving system mainly includes an integrated differential coil, MOSFET-based duplexer, series LCR signal processing circuit, and ultralow noise lithium battery power. To verify the effect of the receiving system we designed, a sand sample moisture content test experiment has been conducted. The experimental results show that the NMR logging system can measure the water content accurately and reflect the distribution of porosity of the sample. The comparison with other small-diameter NMR logging systems shows that the receiving system we designed has a good receiving effect and is close to the level of commercial equipment. Finally, we expect such instruments to play an important role in the evaluation of pollution on the shallow surface.

Reservoir evaluation method for complex resistivity using the borehole–surface electromagnetic method: A case study of an igneous reservoir in the K exploration area, China

Electrical well-logging techniques, combined with electrical conductivity models, have been widely used to estimate oil saturation levels in hydrocarbon reservoirs. For complicated and heterogeneous petroleum reservoirs, however, evaluation results are inevitably limited by well locations. Recent studies have indicated that the borehole–surface electromagnetic method (BSEM) can detect electrical characteristics distal from a well, and it can be applied to delineate the boundaries of complicated reservoirs. Therefore, in the study described here, a new method to estimate reservoir oil saturation, based on the BSEM, has been developed. In this work, we deployed the BSEM in a designated study area, obtaining complex resistivity and polarizability data, through the constrained inversion of the re-weighted regularized conjugate gradient method. Based on the petrophysical analyses, we developed a new saturation evaluation model, composed of a parallel circuit connection between formation water and the polarization induced by the porous medium containing clay minerals. The effectiveness of the new model was verified with a synthetic dataset generated using Archie's law and the improved Dias model. We found that the target reservoir oil saturation results calculated using the new oil saturation model were in good agreement with applicable nuclear magnetic resonance log data, thus verifying the validity of this new BSEM evaluation technique.

Estimation of the Resistivity Index via Nuclear Magnetic Resonance Log Data Based on Fractal Theory

The resistivity index is an important parameter for determining the rock saturation index. However, the saturation index changes greatly in unconventional reservoirs, which leads to oil saturation estimation with great difficulty. Hence, we try to establish the relationship between the resistivity index and log data. Firstly, a novel model of estimating the resistivity index with T 2 time was derived based on fractal theory, the relationship between nuclear magnetic resonance (NMR) T 2 spectrum and capillary pressure curve ( T 2 - P c ), and Archie formula. It regards the logarithm of the resistivity index as the dependent variable, with T 2 time and T 2 time when water saturation is 100% as the independent variables. Second, 17 cores were drilled, and T 2 spectrum and the relationship between the resistivity index and water saturation ( I r - S w ) were jointly measured. Next, the experimental results were substituted into the established model to get the model parameters via the multivariate statistics regression method. Then, the experimental data engaged and not engaged in modeling were used to test the established model. The average relative errors of estimated resistivity indices and experimental results are smaller than 8%, and those of the regressed saturation index are smaller than 5%. Finally, the established model was applied in log data processing and interpretation with good effects. It thus proves that the method of the estimating resistivity index with T 2 time is reliable, which provides a novel solution for determining rock electrical parameter of unconventional reservoirs.

Investigation the relationship between nuclear magnetic resonance and acoustic velocity for improving the evaluation of tight gas reservoirs

ABSTRACT Nuclear magnetic resonance (NMR) and acoustic logging play different roles in formation evaluation. Establishing a relationship model between the two is helpful for joint inversion or evaluation of the physical properties of the formation content. The rock pore structure is used as a link to analyze the theoretical relationship between the transverse relaxation time (T2) spectrum of NMR and acoustic velocity. In this paper, the relationship between NMR T2 and shear-wave velocity is determined by using NMR-acoustic velocity joint experiment. Considering that both NMR T2 spectrum and Shear-wave velocity (Vs) are highly related to porosity and pore structure, a formula based on the relationship between Vs and T2gm (NMR T2 geometric mean) was established. It is found that the T2gm is a power function of the shear-wave velocity. The respective coefficients in this formula for different lithologies were derived through petrophysical measurements of core samples (both NMR and ultrasonic experiments). The relationship model displays the same power-law relations as fitting expression from the experimental data.After that, there is a relation-model application for field data further validated effectiveness and reliability by contrasting the Shear-wave velocity determined by NMR logging with the direct measurements. This model establishment also helps to predict the mutual prediction of NMR and acoustic information of rocks. Based on the sensitivity of the vertical and transverse wave ratios of the formation to the gas-bearing properties of the reservoir, a NMR-acoustic velocity joint gas-bearing identification map was established. An extended case study demonstrated that the cross-plot between NMR logging and acoustic logging is also applicable to natural gas-bearing reservoir identification. As an important supplement and perfection of the existing methods, the relation model proposed in this paper offers a new thought for the petrophysical and in-situ field studies.

Assessment of gas hydrate reservoir from inverted seismic impedance and porosity in the northern Hikurangi margin, New Zealand

Hikurangi margin, New Zealand, the shallowest subduction zone on Earth is the unique place to study the slow slip creep-like deformation and seafloor failure, and their probable link to the presence of gas hydrate, cold seeps and fluid migration. International Ocean Discovery Program expedition 372 discovered gas hydrate within thin intervals (ranging from ~5 to 25 m) of the deformed sediments in the Tuaheni landslide complex area of the northern Hikurangi margin. Seismic profiles show typical BSRs (bottom simulating reflectors) cutting across the dipping strata throughout the sections. To characterize the reservoir, here, we invert both acoustic impedance (product of velocity and density) and porosity along two perpendicular seismic profiles crossing the well using a model-based post-stack seismic inversion technique. Results show the layer structure of alternate high-impedance with low-porosity and low-impedance with high-porosity sediments. Interestingly, each layer is consisting of thin and relatively low impedance intra-layers, which clearly indicates the possible pathways for fluid and gas migration, and one of the reasons for seafloor collapse in this region. Very low impedance observed below the BSR is due to the gas-charged sediments at the dipping strata, and is the probable source of free-gas migrating upward. Next, we apply rock physics theory to know the distribution of gas hydrate at Site U1517 as well as along two perpendicular seismic profiles. Rock physics modeling using sonic velocity at well location shows that gas hydrate is distributed mainly within the depth intervals of 5–50 m, 90–115 m and 130–155 m with an average saturation of about 10–15% and the maximum concentration of about 35% of the pore space at 100 m depth. Prediction of gas hydrate saturation from the resistivity method using neutron porosity and NMR (nuclear magnetic resonance) logs in Archie's empirical formula shows less saturation compared to that from the sonic log. Whereas, estimated gas hydrate saturation from the chloride concentrations ranges from 0 to 45% of the pore space. The spatial distributions of gas hydrate along seismic profiles are predicted by rock physics theory using the inverted impedance and porosity. Saturation of gas hydrate along the seismic profiles varies from 0 to 40% with an average of ~10% of the pore space. The correlation between inverted impedance and porosity indicates that the high impedance layers are due to low porosity consolidated sediment without significant gas hydrate concentration. Gas hydrate is distributed in relatively high porosity and low impedance layers along the seismic profiles. Our result shows that the amount of gas hydrate concentration is low in this region and sediments are highly deformed/disturbed in the presence of many fluid/gas migration pathways.

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.

Reservoir Characteristics of the Lower Jurassic Lacustrine Shale in the Eastern Sichuan Basin and Its Effect on Gas Properties: An Integrated Approach

The exploration of shale gas in Fuling area achieved great success, but the reservoir characteristics and gas content of the lower Jurassic lacustrine in the northern Fuling areas remain unknown. We conducted organic geochemical analyses, Field Emission Scanning Electron Microscope (FE-SEM), X-ray diffraction (XRD) analysis, high-pressure mercury intrusion (MIP) and CH4adsorption experimental methods, as well as NMR logging, to study mineral composition, geochemical, pore structure characteristics of organic-rich shales and their effects on the methane adsorption capacity. The Da’anzhai shale member is generally a set of relatively thick (avg. 75 m) and high carbonate-content (avg. 56.89%) lacustrine sediments with moderate total organic carbon (TOC) (avg. 1.12%) and thermal maturation (Vitrinite reflectance (VR): avg. 1.19%). Five types of lithofacies can be classified: marl (ML), calcareous shale (CS), argillaceous shale (AS), muddy siltstone (MS), and silty shale (SS). CS has good reservoir quality with a high porosity (avg. 4.72%). The small pores with the transverse relaxation time of 0.6–1 ms and 1–3 ms comprised the major part of the porosity in the most lithofacies from Nuclear magnetic resonance (NMR) data, while the large pore (>300 ms) accounts for a small porosity proportion in the CS. The pores mainly constitute of mesopores (avg. 23.2 nm). The clay minerals with a large number of interparticle pores in the SEM contributes most to surface area in the shale lithofacies with a moderate TOC. The adsorption potential of shale samples is huge with an average adsorption capacity of 4.38 mL/g and also has high gas content (avg. 1.04 m3/t). The adsorption capacity of shale samples increases when TOC increases and temperature decreases. Considered reservoir properties and gas properties, CS with the laminated structures in the medium-upper section of the Da’anzhai member is the most advantage lithofacies for shale gas exploitation.

Fine-grained gas hydrate reservoir properties estimated from well logs and lab measurements at the Shenhu gas hydrate production test site, the northern slope of the South China sea

Gas hydrate reservoir properties provide critical information on the controlling mechanisms of gas hydrate formation and accumulation in natural depositional environments. They also are essential to understanding and accurately predicting gas production characteristics. However, the properties of fine-grained reservoirs that host hydrates are poorly studied.Guangzhou Marine Geological Survey acquired a comprehensive set of logging-while-drilling (LWD) logs, in situ tests, and lab measurements from 2015 to 2018 in the W11-17 fine-grained, gas hydrate reservoir of the Shenhu on the South China Sea. Porosity, hydrate saturation, and gas saturation were derived from neutron porosity, nuclear magnetic resonance (NMR), and electrical resistivity logs of SH-W17 and SHSC-4J1 wells and compared with lab measurements of pressurized cores. Units A to C contain three hydrate-concentrated intervals, with a maximum thickness of 32 m and an average hydrate saturation of 0.32 ±0.05. The hydrate saturation was estimated using resistivity and NMR models. Units D and E were inferred to be approximately 20 m thick, free-gas layers containing gas hydrates. Compared to hydrate saturation, the estimations of gas saturation from resistivity and NMR models are less reliable with a range of 0.05–0.4 due to the coexistence of gas hydrates and free gas.Permeabilities estimated from the NMR log agree well with those from neuron porosity in non-hydrate bearing intervals but are slightly higher in hydrate-bearing intervals. By incorporating the lab measurements and in situ tests into the NMR pore-size analysis, the permeability of water-bearing sediments in the hydrate intervals in the SHSC-4J1 well can be constrained to the range of 0.002–0.1 md, with 0.015 md being our best estimate. The NMR pore-size geometries indicate gas hydrates appear to preferentially fill bigger pores within fine-grained reservoirs, which exhibit a similar behavior to coarse-grained reservoirs. Our resistivity and relative permeability modeling indicate that the growth of gas hydrates within pore spaces is characterized by pore-filling and cementation behaviors.

Integrated petrophysical evaluation of the Lower Middle Bakken Member in the Viewfield Pool, southeastern Saskatchewan, Canada

The Viewfield Pool of the Lower Middle Bakken Member, the largest light oil pool in Saskatchewan, Canada has been described as an unconventional resource play. Reservoir evaluation in this pool has been challenging because of low permeability, complex lithology and reservoir heterogeneity. To address the difficulties, this study employed an integrated approach to derive reservoir parameters and provided a detailed petrophysical characterization of the Viewfield Middle Bakken play, which led to a division of Unit A, the Lower Middle Bakken Member into two subunits: A1 for the lower interval and A2 for the upper interval. Petrophysical models were developed based on thorough analyses of core measurements, conventional well logs and available advanced nuclear magnetic resonance (NMR) well log data. The proposed models were applied to determine reservoir properties including shale content, porosity, permeability and water saturation for the two subunits in 163 vertical wells among which three have NMR logs. The results reveal that subunits A1 and A2 differ significantly in petrophysical properties and reservoir quality. A2, the very fine-grained dolomitic sandstone subunit has larger pore size, higher porosity and permeability, lower shale content and water saturation, and thus represents the preferred interval for oil production across the Viewfield Bakken Pool area and has greater resource potential than the siltstone subunit A1. The mapped petrophysical properties show spatial trends that align well with the previously recognized regional geological features. Favourable potential high productivity zones can be outlined by the areas of intersection of all essential reservoir parameters above defined threshold values.

Downhole nuclear magnetic resonance logging in glaciomarine sediments near Ottawa, Ontario, Canada

ABSTRACTDownhole nuclear magnetic resonance technology was applied in four boreholes intersecting glaciomarine sediments of the Ottawa Valley, Ontario. The study evaluated the ability of slim‐hole nuclear magnetic resonance tools to measure in situ volumetric water contents (porosities in saturated sediments) for geohazard and hydrogeological applications. The sediments are composed of clay‐ and silt‐sized grains of glacially eroded rock flour derived from the Precambrian Shield containing trace amounts of magnetic minerals, and porosities ranging from 40 to 74 porosity units (PU, 1% porosity = 1 PU). Two nuclear magnetic resonance instruments were deployed with echo times of 0.5 and 1.0 ms, and diameters of investigation ranging from 14.0 to 30.5 cm. Quantitative nuclear magnetic resonance porosities in the sediments were typically within ±5 PU (95% within ±10 PU) of core calibration data sets in the silty clays where threshold bulk magnetic susceptibility values were <30 × 10−4 SI. This was found to deviate, however, where the concentration and mineralogy of magnetic particles changed, interpreted to be shortening relaxation times which led to underestimation of true water contents. This effect is correlated with a change in depth from magnetite to superparamagnetic nanoparticles of greigite (low‐temperature iron monosulphide) magnetism, interpreted to occur at the sulphate‐methane interface. Clay mineralogy and pore water chemistry were also examined as contributing factors, but were not found to significantly shorten nuclear magnetic resonance relaxation responses. Very short T2 times (<2 ms) are typical in these particular silty clays, requiring a tool with an echo spacing of <1.0 ms. Due to increased potential for sediment disturbance around a well caused by the geotechnical sensitivity of the sediments, a nuclear magnetic resonance instrument with multiple frequencies provided signal penetration out to various diameters around the tool, giving needed information about the size of the disturbed zone surrounding the casing.

Oil content prediction of lacustrine organic-rich shale from wireline logs: A case study of intersalt reservoirs in the Qianjiang Sag, Jianghan Basin, China

Shale oil is an unconventional oil resource with great potential. Oil saturation ([Formula: see text]) is an essential parameter for formation evaluation. However, due to the complexity of matrix mineral components and pore structure, Archie’s law cannot be used directly to calculate [Formula: see text] in shale oil reservoirs. We have developed a new saturation model for shale oil reservoirs. This model allows us to separate the organic from the inorganic pores, eliminate the background conductivity mainly caused by the borehole fluid or conductive minerals and determine the effective conductive porosity, which rules out nonconductive porosity, including isolated pores and the pore space affected by the fluid distribution. By analyzing the logging and core experimental data from the Qianjiang Sag, Jianghan Oilfield, we found that the T2 cutoff porosities of nuclear magnetic resonance logging are strongly related to the nonconductive porosities. After we determine the T2 cutoff value using the core experimental data, we can use it to obtain nonconductive porosity fraction in each depth point, which allows us to efficiently calculate [Formula: see text]. We calculate oil saturation values and use them to estimate the oil content. The results are coherent with the core experimental data, which indicates the efficiency of this model.

Synthesize Nuclear Magnetic Resonance T2 Spectrum From Conventional Logging Responses With Spectrum Regression Forest

Transverse relaxation T2 spectrum obtained by nuclear magnetic resonance (NMR) logging tools is an intuitive reflection of the pore size distribution for subsurface formation, which is valuable for petroleum reservoir characterization. However, the deployment of NMR logging tools is constrained by financial and operational factors, while NMR data are only available in very limited wells. This seriously limits its application in practices. Therefore, researchers try to synthesize NMR T2 spectra from more widely measured conventional logging data with the help of machine learning technologies. In the article, we propose the spectrum regression forest (SRF) algorithm for the prediction of NMR T2 spectra from conventional logging responses. Based on the experiment on the real-world well data of carbonate reservoir, the proposed algorithm is proved to provide effective NMR T2 spectrum predictions with accuracy amplitudes and consist morphology, which is believed to enhance the understanding of formation pore structures for future reservoir characterization practices.

A calibration method for estimating mudcake thickness and porosity using NMR data

Mudcake thickness affects wellbore operations such as differential sticking, well completion, and wellbore clean-up operations. One of the properties for which a drilling fluid is screened during laboratory tests is the thickness of the mudcake it produces. Such laboratory tests are routinely conducted on ceramic discs or rock samples, at a specified temperature and pressure. Mathematical models have also been reported for predicting cake thickness and mud induced formation damage. The problem here is that the conditions upon which both laboratory tests and mathematical models are run do not match all conditions in the wellbore during drilling. Calliper tools can be used to directly quantify mudcake thickness in wellbore, however, they cannot differentiate between a sloughing hole and a mudcake. This study therefore explores the potentiality of nuclear magnetic resonance (NMR) logging tools to measure the thickness and porosity of mudcake, and mud induced formation damage in wellbores. This proposed approach utilizes measurements routinely taken from a multi-frequency NMR logging tool, namely T2 relaxation times at three depth of investigations (DOI). For this specific application, the first DOI captures the mudcake and the near wellbore region, the second DOI captures an inner radius (invaded zone), while the third DOI measures the virgin zone. NMR measurements in these three DOIs were simulated in our laboratory experiments. From the acquired NMR measurements, we identified characteristic T2 – curves for mudcakes and solid infiltration and then defined a workflow to obtain them. The areas under these characteristic T2-curves showed good correlations with the mudcake porosity and thickness. Based on these, several calibration curves were developed for mudcake thicknesses, porosity and formation damage. The calibration curves appear to be robust since they were obtained from a variety of rock types with a wide range of porosity and permeability.

Estimation of oil saturation via pseudo capillary pressure curve from nuclear magnetic resonance log data in tight conglomerate reservoirs

Tight conglomerate reservoirs have complex pore structure and strong heterogeneity which could bring great difficulties in the identification of oil and water layers. In order to solve this problem, the tight conglomerate reservoirs of Triassic Baikouquan Formation and Permian Urho Formation in Mahu Depression, Northwest Junggar Basin in China are selected as the study area. Firstly, 23 representative core plunger samples were selected from 9 wells. The experimental data of helium porosity, permeability, mercury intrusion capillary pressure (MICP) curve, and nuclear magnetic resonance (NMR) T2 spectrum under completely watered condition were measured and analyzed. Secondly, conglomerate reservoir classification criterion was built based on flow zone indicator (FZI). Its classification results conform to the classification of J function and core images. Thirdly, the piecewise power function was adopted to predict the pseudo capillary pressure curve by NMR T2 spectrum and the corresponding models were established via reservoir classification. Fourthly, based on the obtained pseudo capillary pressure curve and average J function curve, a novel method for predicting oil saturation by the ratio of median radius was proposed. Finally, the built models were used to process the experimental data not involved in modeling and log data. The predicting results are well consistent with the experimental results, which indicates the high reliability of the models. The established models are essential for helping the classification of tight conglomerate reservoirs, calculation of reservoir parameters, and identification of oil and water layers.