Advanced fluid-typing methods for NMR logging

In recent years, nuclear magnetic resonance （NMR） has been increasingly used for fluid- typing in well-logging because of the improved generations of NMR logging tools. This paper first discusses the applicable conditions of two one-dimensional NMR methods： the dual TW method and dual TE method. Then, the two-dimensional （T2, D） and （T2, T1） NMR methods are introduced. These different typing methods for hydrocarbon are compared and analyzed by numerical simulation. The results show that the dual TW method is not suitable for identifying a macroporous water layer. The dual TE method is not suitable for typing gas and irreducible water. （T2, T1） method is more effective in typing a gas layer. In an oil-bearing layer of movable water containing big pores, （T2, T1） method can solve the misinterpretation problem in the dual TWmethod between a water layer with big pores and an oil layer. The （T2, T1） method can distinguish irreducible water from oil of a medium viscosity, and the viscosity range of oil becomes wide in contrast with that of the dual TW method. The （T2, D） method is more effective in typing oil and water layers. In a gas layer, when the SNR is higher than a threshold, the （T2, D） method can resolve the overlapping T2 signals of irreducible water and gas that occurs due to the use of the dual TE method. Twodimensional NMR for fluid-typing is an important development of well logging technology.

Corrections for downhole NMR logging

Nuclear magnetic resonance logging （NMR） is an open well logging method. Drilling mud resistivity, formation resistivity and sodium ions influence its radio frequency （RF） field strength and NMR logging signals. Research on these effects can provide an important basis for NMR logging data acquisition and interpretation. Three models, water-based drilling mud--water bearing formation, water- based drilling mud--oil bearing formation, oil-based drilling mud--water bearing formation, were studied by finite element method numerical simulation. The influences of drilling mud resistivity and formation resistivity on the NMR logging tool RF field and the influences of sodium ions on the NMR logging signals were simulated numerically. On the basis of analysis, RF field correction and sodium ion correction formulae were proposed and their application range was also discussed. The results indicate that when drilling mud resistivity and formation resistivity are 0.02 Ω·m and 0.2 Ω·m respectively, the attenuation index of centric NMR logging tool is 8.9% and 9.47% respectively. The RF field of an eccentric NMR logging tool is affected mainly by formation resistivity. When formation resistivity is 0.1 Ω·m, the attenuation index is 17.5%. For centric NMR logging tools, the signals coming from sodium ions can be up to 31.8% of total signal. Suggestions are proposed for further research into NMR logging tool correction method and response characteristics.

Reservoir and lithofacies shale classification based on NMR logging

Shale gas reservoirs have fine-grained textures and high organic contents,leading to complex pore structures.Therefore,accurate well-log derived pore size distributions are difficult to acquire for this unconventional reservoir type,despite their importance.However,nuclear magnetic resonance(NMR)logging can in principle provide such information via hydrogen relaxation time measurements.Thus,in this paper,NMR response curves(of shale samples)were rigorously mathematically analyzed(with an Expectation Maximization algorithm)and categorized based on the NMR data and their geology,respectively.Thus the number of the NMR peaks,their relaxation times and amplitudes were analyzed to characterize pore size distributions and lithofacies.Seven pore size distribution classes were distinguished;these were verified independently with Pulsed-Neutron Spectrometry(PNS)well-log data.This study thus improves the interpretation of well log data in terms of pore structure and mineralogy of shale reservoirs,and consequently aids in the optimization of shale gas extraction from the subsurface.

Coexistence of natural gas hydrate,free gas and water in the gas hydrate system in the Shenhu Area,South China Sea

Shenhu Area is located in the Baiyun Sag of Pearl River Mouth Basin,which is on the northern continental slope of the South China Sea.Gas hydrates in this area have been intensively investigated,achieving a wide coverage of the three-dimensional seismic survey,a large number of boreholes,and detailed data of the seismic survey,logging,and core analysis.In the beginning of 2020,China has successfully conducted the second offshore production test of gas hydrates in this area.In this paper,studies were made on the structure of the hydrate system for the production test,based on detailed logging data and core analysis of this area.As to the results of nuclear magnetic resonance(NMR)logging and sonic logging of Well GMGS6-SH02 drilled during the GMGS6 Expedition,the hydrate system on which the production well located can be divided into three layers:(1)207.8–253.4 mbsf,45.6 m thick,gas hydrate layer,with gas hydrate saturation of 0–54.5%(31%av.);(2)253.4–278 mbsf,24.6 m thick,mixing layer consisting of gas hydrates,free gas,and water,with gas hydrate saturation of 0–22%(10%av.)and free gas saturation of 0–32%(13%av.);(3)278–297 mbsf,19 m thick,with free gas saturation of less than 7%.Moreover,the pore water freshening identified in the sediment cores,taken from the depth below the theoretically calculated base of methane hydrate stability zone,indicates the occurrence of gas hydrate.All these data reveal that gas hydrates,free gas,and water coexist in the mixing layer from different aspects.

Reservoir rock properties estimation based on conventional and NMR log data using ANN-Cuckoo:A case study in one of super fields in Iran southwest

This work highlights the application of Artificial Neural Networks optimized by Cuckoo optimization algorithm for predictions of NMR log parameters including porosity and permeability by using field log data.The NMR logging data have some highly vital privileges over conventional ones.The measured porosity is independent from bearer pore fluid and is effective porosity not total.Moreover,the permeability achieved by exact measurement and calculation considering clay content and pore fluid type.Therefore availability of the NMR data brings a great leverage in understanding the reservoir properties and also perfectly modelling the reservoir.Therefore,achieving NMR logging data by a model fed by a far inferior and less costly conventional logging data is a great privilege.The input parameters of model were neutron porosity(NPHI),sonic transit time(DT),bulk density(RHOB)and electrical resistivity(RT).The outputs of model were also permeability and porosity values.The structure developed model was build and trained by using train data.Graphical and statistical validation of results showed that the developed model is effective in prediction of field NMR log data.Outcomes show great possibility of using conventional logging data be used in order to reach the precious NMR logging data without any unnecessary costly tests for a reservoir.Moreover,the considerable accuracy of newly ANN-Cuckoo method also demonstrated.This study can be an illuminator in areas of reservoir engineering and modelling studies were presence of accurate data must be essential.

A New Empirical Method for Constructing Capillary Pressure Curves from Conventional Logs in Low-Permeability Sandstones

Pore structure reflected from capillary pressure curves plays an important role in low-permeability formation evaluation. It is a common way to construct capillary pressure curves by Nuclear Magnetic Resonance（NMR） log. However, the method＇s efficiency will be severely affected if there is no NMR log data or it cannot reflect pore structure well. Therefore, on the basis of J function and diagenetic facies classification, a new empirical model for constructing capillary pressure curves from conventional logs is proposed here as a solution to the problem. This model includes porosity and the relative value of natural gamma rays as independent variables and the saturation of mercury injection as a dependent variable. According to the 51 core experimental data sets of three diagenetic facies from the bottom of the Upper Triassic in the western Ordos Basin, China, the model＇s parameters in each diagenetic facies are calibrated. Both self-checking and extrapolation tests show a positive effect, which demonstrates the high reliability of the proposed capillary pressure curve construction model. Based on the constructed capillary pressure curves, NMR T_2 spectra under fully brine-saturated conditions are mapped by a piecewise power function. A field study is then presented. Agreement can be seen between the mapped NMR T_2 spectra and the MRIL-Plog data in the location of the major peak, right boundary, distribution characteristics and T_2 logarithmic mean value. In addition, the capillary pressure curve construction model proposed in this paper is not affected by special log data or formation condition. It is of great importance in evaluating pore structure, predicting oil production and identifying oil layers through NMR log data in low-permeability sandstones.