Fluid identification and tight oil layer classification for the southwestern Mahu Sag,Junggar Basin using NMR logging-based spectrum decomposition

The intricate distribution of oil and water in tight rocks makes pinpointing oil layers challenging.While conventional identification methods offer potential solutions,their limited accuracy precludes them from being effective in their applications to unconventional reservoirs.This study employed nuclear magnetic resonance(NMR)spectrum decomposition to dissect the NMR T_(2)spectrum into multiple subspectra.Furthermore,it employed laboratory NMR experiments to ascertain the fluid properties of these sub-spectra,aiming to enhance identification accuracy.The findings indicate that fluids of distinct properties overlap in the T_(2)spectra,with bound water,movable water,bound oil,and movable oil appearing sequentially from the low-value zone to the high-value zone.Consequently,an oil layer classification scheme was proposed,which considers the physical properties of reservoirs,oil-bearing capacity,and the characteristics of both mobility and the oil-water two-phase flow.When applied to tight oil layer identification,the scheme's outcomes align closely with actual test results.A horizontal well,deployed based on these findings,has produced high-yield industrial oil flow,underscoring the precision and dependability of this new approach.

P-SV wave elastic impedance and fluid identification factor in weakly anisotropic media

The P-SV wave reflection coefficients in VTI and HTI media were obtained by approximation of the Jilek（2002a and b）equation in orthotropic anisotropic media.An approximate equation for P-SV wave elastic impedance can be derived from the combination of the new coefficients with S-wave elastic impedance（Duffaut et al.,2000）.On this basis, the fluid identification factor in weakly anisotropic media was constructed and used to identify the Castagna and Smith（1994）lithologic combination and achieved good results. Finally,we specifically analyzed the anisotropic parameter impacts P-SV wave elastic impedance and fluid factor trends.

Zoeppritz equation-based prestack inversion and its application in fluid identification

Prestack seismic inversion methods adopt approximations of the Zoeppritz equations to describe the relation between reflection coefficients and P-wave velocity, S-wave velocity, and density. However, the error in these approximations increases with increasing angle of incidence and variation of the elastic parameters, which increases the number of inversion solutions and minimizes the inversion accuracy. In this study, we explore a method for solving the reflection coefficients by using the Zoeppritz equations. To increase the accuracy of prestack inversion, the simultaneous inversion of P-wave velocity, S-wave velocity, and density by using prestack large-angle seismic data is proposed based on generalized linear inversion theory. Moreover, we reduce the ill posedness and increase the convergence of prestack inversion by using the regularization constraint damping factor and the conjugate gradient algorithm. The proposed prestack inversion method uses prestack large-angle seismic data to obtain accurate seismic elastic parameters that conform to prestack seismic data and are consistent with logging data from wells.

Fluid identification based on frequency-dependent AVO attribute inversion in multi-scale fracture media

A key problem in seismic inversion is the identification of the reservoir fluids. Elastic parameters, such as seismic wave velocity and formation density, do not have sufficient sensitivity, thus, the conventional amplitude-versus-offset（AVO） method is not applicable. The frequency-dependent AVO method considers the dependency of the seismic amplitude to frequency and uses this dependency to obtain information regarding the fluids in the reservoir fractures. We propose an improved Bayesian inversion method based on the parameterization of the Chapman model. The proposed method is based on 1） inelastic attribute inversion by the FDAVO method and 2） Bayesian statistics for fluid identification. First, we invert the inelastic fracture parameters by formulating an error function, which is used to match observations and model data. Second, we identify fluid types by using a Markov random field a priori model considering data from various sources, such as prestack inversion and well logs. We consider the inelastic parameters to take advantage of the viscosity differences among the different fluids possible. Finally, we use the maximum posteriori probability for obtaining the best lithology/fluid identification results.

Fluid identification and effective fracture prediction based on frequency-dependent AVOAz inversion for fractured reservoirs

Fluid and effective fracture identification in reservoirs is a crucial part of reservoir prediction.The frequency-dependent AVO inversion algorithms have proven to be effective for identifying fluid through its dispersion property.However,the conventional frequency-dependent AVO inversion algorithms based on Smith&Gidlow and Aki&Richards approximations do not consider the acquisition azimuth of seismic data and neglect the effect of seismic anisotropic dispersion in the actual medium.The aligned fractures in the subsurface medium induce anisotropy.The seismic anisotropy should be considered while accounting for the seismic dispersion properties through fluid-saturated fractured reservoirs.Anisotropy in such reservoirs is frequency-related due to wave-induced fluid-flow(WIFF)between interconnected fractures and pores.It can be used to identify fluid and effective fractures(fluid-saturated)by using azimuthal seismic data via anisotropic dispersion properties.In this paper,based on Rüger’s equation,we derived an analytical expression in the frequency domain for the frequencydependent AVOAz inversion in terms of fracture orientation,dispersion gradient of isotropic background rock,anisotropic dispersion gradient,and the dispersion at a normal incident angle.The frequency-dependent AVOAz equation utilizes azimuthal seismic data and considers the effect of both isotropic and anisotropic dispersion.Reassigned Gabor Transform(RGT)is used to achieve highresolution frequency division data.We then propose the frequency-dependent AVOAz inversion method to identify fluid and characterize effective fractures in fractured porous reservoirs.Through application to high-qualified seismic data of dolomite and carbonate reservoirs,the results show that the method is useful for identifying fluid and effective fractures in fluid-saturated fractured rocks.

A new method for reservoir fluid identification

The wavelet transform （WT） method has been employed to decompose an original geophysical signal into a series of components containing different information about reservoir features such as pore fluids, lithology, and pore structure. We have developed a new method based on WT energy spectra analysis, by which the signal component reflecting the reservoir fluid property is extracted. We have successfully processed real log data from an oil field in central China using this method. The results of the reservoir fluid identification agree with the results of well tests.

Crack fluid identification of shale reservoir based on stress-dependent anisotropy

Shale reservoirs are typically very tight, and crack are only a small part of the reservoir. The directional arrangement of cracks leads to the anisotropic characteristics of shale, and the type of fluid filled in cracks affects the shale reservoir evaluation and late development. Many rock physics theories and methods typically use second-and fourthorder crack density tensors to characterize the elastic anisotropy induced by cracks as well as the normal-to-tangential crack compliance ratio to distinguish between dry and saturated cracks. This study def ines an anisotropic crack f luid indicator for vertical transversely isotropy(VTI) media with vertical symmetry axis which is the integration of the normal-to-tangential crack compliance ratio in three directions. A new dimensionless fourth-order tensor, including crack f luid type, azimuth distribution, and geometric shape, is constructed by substituting the normal and tangential compliance into the fourth-order crack density tensor, which can also be used to identify the type of crack fluid in the VTI media. Using the Callovo–Oxfordian shale experimental data, the variation of the elastic properties of dry and saturated shale samples with axial stress is analyzed. The results demonstrate that the anisotropic crack f luid indicator of water-bearing shale samples is less than that of the dry shale samples and that the dimensionless fourth-order tensor of water-bearing shale samples is nearly one order of magnitude greater than that of the dry shale samples. Therefore, the anisotropic crack f luid indicator and dimensionless fourth-order tensor can ref lect the crack f luid type in shale samples and can be used for shale reservoir prediction and f luid identif ication.

Seismic description and fluid identification of thin reservoirs in Shengli Chengdao extra-shallow sea oilfield

The meandering channel deposit of the upper member of Neogene Guantao Formation in Shengli Chengdao extra-shallow sea oilfield is characterized by rapid change in sedimentary facies.In addition,affected by surface tides and sea water reverberation,the double sensor seismic data processed by conventional methods has low signal-to-noise ratio and low resolution,and thus cannot meet the needs of seismic description and oil-bearing fluid identification of thin reservoirs less than 10 meters thick in this area.The two-step high resolution frequency bandwidth expanding processing technology was used to improve the signal-to-noise ratio and resolution of the seismic data,as a result,the dominant frequency of the seismic data was enhanced from 30 Hz to 50 Hz,and the sand body thickness resolution was enhanced from 10 m to 6 m.On the basis of fine layer control by seismic data,three types of seismic facies models,floodplain,natural levee and point bar,were defined,and the intelligent horizon-facies controlled recognition technology was worked out,which had a prediction error of reservoir thickness of less than 1.5 m.Clearly,the description accuracy of meandering channel sand bodies has been improved.The probability semi-quantitative oiliness identification method of fluid by prestack multi-parameters has been worked out by integrating Poisson’s ratio,fluid factor,product of Lame parameter and density,and other prestack elastic parameters,and the method has a coincidence rate of fluid identification of more than 90%,providing solid technical support for the exploration and development of thin reservoirs in Shengli Chengdao extra-shallow sea oilfield,which is expected to provide reference for the exploration and development of similar oilfields in China.

A new method for fluid identification and saturation calculation of low contrast tight sandstone reservoir

The resistivity difference between oil and gas layers and the water layers in low contrast tight sandstone reservoirs is subtle. Fluid identification and saturation calculation based on conventional logging methods are facing challenges in such reservoirs. In this paper, a new method is proposed for fluid identification and saturation calculation in low contrast tight sandstone reservoirs. First, a model for calculating apparent formation water resistivity is constructed, which takes into account the influence of shale on the resistivity calculation and avoids apparent formation water resistivity abnormal values.Based on the distribution of the apparent formation water resistivity obtained by the new model, the water spectrum is determined for fluid identification in low contrast tight sandstone reservoirs.Following this, according to the average, standard deviation, and endpoints of the water spectrum, a new four-parameter model for calculating reservoir oil and gas saturation is built. The methods proposed in this paper are applied to the low contrast tight sandstone reservoirs in the Q4 formation of the X53 block and X70 block in the south of Songliao Basin, China. The results show that the water spectrum method can effectively distinguish oil-water layers and water layers in the study area. The standard deviation of the water spectrum in the oil-water layer is generally greater than that in the water layer. The new four-parameter model yields more accurate oil and gas saturation. These findings verify the effectiveness of the proposed methods.

Fluid identification method and application of pre-stack and poststack integration based on seismic low-frequency

Seismic low-frequency component included more fluid information,which was still a focus in geophysics.Seismic pre-stack data contained more fluid information,but signal to noise ratio(SNR)was low.By comparison,seismic post-stack data had a high SNR,but some fluid information was lost during data processing.Different angel stacks reflected different fluid seismic amplitude,compared with nearangle stacks.Far angle stacks had more low frequency components,which were more benefit for fluid identification.Based on this principle,combined with the pre-stacks and post-stacks seismic data,more fluid information would be included.In this study,a new fluid identification method was proposed.This method combined the post-stack seismic and pre-stack seismic data,it took into consideration high SNR of the post-stack seismic data and the large fluid amplitude differences of the pre-stack different angles.Field testing indicated this method was quite effective in detecting fluids.

Identification of Mixtures of Two Types of Body Fluids Using the Multiplex Methylation System and Random Forest Models

Objective Body fluid mixtures are complex biological samples that frequently occur in crime scenes,and can provide important clues for criminal case analysis.DNA methylation assay has been applied in the identification of human body fluids,and has exhibited excellent performance in predicting single-source body fluids.The present study aims to develop a methylation SNaPshot multiplex system for body fluid identification,and accurately predict the mixture samples.In addition,the value of DNA methylation in the prediction of body fluid mixtures was further explored.Methods In the present study,420 samples of body fluid mixtures and 250 samples of single body fluids were tested using an optimized multiplex methylation system.Each kind of body fluid sample presented the specific methylation profiles of the 10 markers.Results Significant differences in methylation levels were observed between the mixtures and single body fluids.For all kinds of mixtures,the Spearman’s correlation analysis revealed a significantly strong correlation between the methylation levels and component proportions(1:20,1:10,1:5,1:1,5:1,10:1 and 20:1).Two random forest classification models were trained for the prediction of mixture types and the prediction of the mixture proportion of 2 components,based on the methylation levels of 10 markers.For the mixture prediction,Model-1 presented outstanding prediction accuracy,which reached up to 99.3%in 427 training samples,and had a remarkable accuracy of 100%in 243 independent test samples.For the mixture proportion prediction,Model-2 demonstrated an excellent accuracy of 98.8%in 252 training samples,and 98.2%in 168 independent test samples.The total prediction accuracy reached 99.3%for body fluid mixtures and 98.6%for the mixture proportions.Conclusion These results indicate the excellent capability and powerful value of the multiplex methylation system in the identification of forensic body fluid mixtures.

Body Fluid Identification by Messenger RNA Profiling in Sexual Assault

Body fluid identification through messenger RNA(mRNA)has been proposed as a useful supplement to presumptive and confirmatory tests by previous laboratory studies;however,its application in routine clinical forensic examination was rare.We report a case of sexual assault in which body fluid identification by mRNA profiling was used.Vaginal secretions mRNA markers(MUC4,HBD1,and CYP2B7P1)were used to test the sample,being obtained positive results.This case demonstrates that mRNA profiling of body fluids could be applied to routine case examinations as an aid,acting as a scientific collaborative evidence to strengthen the medicolegal opinion.

Application of fluid modulus inversion to complex lithology reservoirs in deep-water areas

It has been a challenge to distinguish between seismic anomalies caused by complex lithology and hydrocarbon reservoirs using conventional fluid identification techniques,leading to difficulties in accurately predicting hydrocarbon-bearing properties and determining oil-water contacts in reservoirs.In this study,we built a petrophysical model tailored to the deep-water area of the Baiyun Sag in the eastern South China Sea based on seismic data and explored the feasibility of the tri-parameter direct inversion method in the fluid identification of complex lithology reservoirs,offering a more precise alternative to conventional techniques.Our research found that the fluid modulus can successfully eliminate seismic amplitude anomalies caused by lithological variations.Furthermore,the seismic databased direct inversion for fluid modulus can remove the cumulative errors caused by indirect inversion and the influence of porosity.We discovered that traditional methods using seismic amplitude anomalies were ineffective in detecting fluids,determining gas-water contacts,or delineating high-quality reservoirs.However,the fluid factor Kf,derived from solid-liquid decoupling,proved to be sensitive to the identification of hydrocarbon-bearing properties,distinguishing between high-quality and poor-quality gas zones.Our findings confirm the value of the fluid modulus in fluid identification and demonstrate that the tri-parameter direct inversion method can significantly enhance hydrocarbon exploration in deep-water areas,reducing associated risks.

Seismic low-frequency-based calculation of reservoir fluid mobility and its applications

Low frequency content of seismic signals contains information related to the reservoir fluid mobility. Based on the asymptotic analysis theory of frequency-dependent reflectivity from a fluid-saturated poroelastic medium, we derive the computational implementation of reservoir fluid mobility and present the determination of optimal frequency in the implementation. We then calculate the reservoir fluid mobility using the optimal frequency instantaneous spectra at the low-frequency end of the seismic spectrum. The methodology is applied to synthetic seismic data from a permeable gas-bearing reservoir model and real land and marine seismic data. The results demonstrate that the fluid mobility shows excellent quality in imaging the gas reservoirs. It is feasible to detect the location and spatial distribution of gas reservoirs and reduce the non-uniqueness and uncertainty in fluid identification.

Fluid sensitivity study of elastic parameters in lowmedium porosity and permeability reservoir rocks

In this article,based on the acoustic measurements of core samples obtained from the low to medium porosity and permeability reservoirs in the WXS Depression,the densities and P and S wave velocities of these core samples were obtained.Then based on these data,a series of elastic parameters were computed.From the basic theory and previous pore fluid research results,we derived a new fluid identification factor（F）.Using the relative variations,Ag/w and Ao/w,of the elastic parameters between gas and water saturated samples and between oil and water saturated samples,λρ,σHSFIF,Kρ,λρ-2μρ,and F as quantitative indicators,we evaluate the sensitivity of the different fluid identification factors to identify reservoir fluids and validate the effects by crossplots.These confirm that the new fluid identification factor（F） is more sensitive for distinguishing oil and water than the traditional method and is more favorable for fliud identification in low to medium porosity and permeability reservoirs.

A decomposition method of nuclear magnetic resonance T2 spectrum for identifying fluid properties

Based on analysis of NMR T2 spectral characteristics,a new method for identifying fluid properties by decomposing T2 spectrum through signal analysis has been proposed.Because T2 spectrum satisfies lognormal distribution on transverse relaxation time axis,the T2 spectrum can be decomposed into 2 to 5 independent component spectra by fitting the T2 spectrum with Gauss functions.By analyzing the free relaxation response characteristics of crude oil and formation water,the dynamic response characteristics of the core mutual drive between oil and water,the petrophysical significance of each component spectrum is clarified.T2 spectrum can be decomposed into clay bound water component spectrum,capillary bound fluid component spectrum,micropores fluid component spectrum and macropores fluid component spectrum.According to the nature of crude oil in the target area,the distribution range of T2 component spectral peaks of oil-bearing reservoir is 165-500 ms on T2 time axis.This range can be used to accurately identify fluid properties.This method has high adaptability in identifying complex oil and water layers in low porosity and permeability reservoirs.

Fluids discrimination by ray-path elastic impedance inversion: A successful case from Sulige tight gas field

Existing seismic prediction methods struggle to effectively discriminate between fluids in tight gas reservoirs,such as those in the Sulige gas field in the Ordos Basin,where porosity and permeability are extremely low and the relationship between gas and water is complicated.In this paper,we have proposed a comprehensive seismic fluid identification method that combines ray-path elastic impedance(REI)inversion with fluid substitution for tight reservoirs.This approach is grounded in geophysical theory,forward modeling,and real data applications.We used geophysics experiments in tight gas reservoirs to determine that Brie's model is better suited to calculate the elastic parameters of mixed fluids than the conventional Wood’s model.This yielded a more reasonable and accurate fluid substitution model for tight gas reservoirs.We developed a forward model and carried out inversion of REI.which reduced the non-uniqueness problem that has plagued elastic impedance inversion in the angle domain.Our well logging forward model in the ray-path domain with different fluid saturations based on a fluid substitution model proved that REI identifies fluids more accurately when the ray parameters are large.The distribution of gas saturation can be distinguished from the crossplot of REI(p=0.10)and porosity.The inverted ray-path elastic impedance profile was further used to predict the porosity and gas saturation profile.Our new method achieved good results in the application of 2D seismic data in the western Sulige gas field.

The applicability and underlying factors of frequency-dependent amplitude-versus-offset(AVO)inversion

Recently,the great potential of seismic dispersion attributes in oil and gas exploration has attracted extensive attention.The frequency-dependent amplitude versus offset(FAVO)technology,with dispersion gradient as a hydrocarbon indicator,has developed rapidly.Based on the classical AVO theory,the technology works on the assumption that elastic parameters are frequency-dependent,and implements FAVO inversion using spectral decomposition methods,so that it can take dispersive effects into account and effectively overcome the limitations of the classical AVO.However,the factors that affect FAVO are complicated.To this end,we construct a unified equation for FAVO inversion by combining several Zoeppritz approximations.We study and compare two strategies respectively with(strategy 1)and without(strategy 2)velocity as inversion input data.Using theoretical models,we investigate the influence of various factors,such as the Zoeppritz approximation used,P-and S-wave velocity dispersion,inversion input data,the strong reflection caused by non-reservoir interfaces,and the noise level of the seismic data.Our results show that FAVO inversion based on different Zoeppritz approximations gives similar results.In addition,the inversion results of strategy 2 are generally equivalent to that of strategy 1,which means that strategy 2 can be used to obtain dispersion attributes even if the velocity is not available.We also found that the existence of non-reservoir strong reflection interface may cause significant false dispersion.Therefore,logging,geological,and other relevant data should be fully used to prevent this undesirable consequence.Both the P-and S-wave related dispersion obtained from FAVO can be used as good indicators of a hydrocarbon reservoir,but the P-wave dispersion is more reliable.In fact,due to the mutual coupling of P-and S-wave dispersion terms,the P-wave dispersion gradient inverted from PP reflection seismic data has a stronger hydrocarbon detection ability than the S-wave dispersion gradient.Moreover,there is little difference in using post-stack data or pre-stack angle gathers as inversion input when only the P-wave dispersion is desired.The real application examples further demonstrate that dispersion attributes can not only indicate the location of a hydrocarbon reservoir,but also,to a certain extent,reveal the physical properties of reservoirs.

Application of Multi-Attribute Crossplots to Tight Gas in X Area, Western China

The gas-bearing reservoir in X area is mainly the tight sandstone reservoir characterized by low porosity and permeability, frequently lateral variation and poor connectivity of single sand. The previous research results reveal that the general seismic attributes analysis cannot meet the requirement of fluid identification. This is because the relationship between seismic attributes and their implication is uncertain and ambiguous, which decreases the precision of both reservoir prediction and fluid identification. To overcome the problem, multi-attribute crossplot technology is proposed from the mathematical statistical point of view rather than the correspondence between the seismic attributes and their geological implication. In this method, the wells which have the same statistical law are classified firstly, and then all the interest wells are retained while the wells beyond the statistical law are eliminated, and the seismic attributes sensitive to the same types of eliminated wells are optimized and used to generate crossplots. The nonzero area of their crossplots results just predicts the potential distribution. The discontinuity of subsurface geological conditions results in the non-continuous shape and the seismic bin lead to the mosaic form. The optimization of sensitive attributes relative to the same types of wells is independent from each other, and thus the order of attributes in crossplots does not affect the final prediction results. This method is based on the statistical theory and suitable for the areas such as the study area abundant of lots of well data. Application to X area proves the effectiveness of this method and predicts plane distribution about different types of gas production. Due to the effect of faults and other geological factors, the partition prediction results using multi-attribute crossplots reach 95% of coincidence which is obviously and far higher than the results of the whole area. The final prediction results show that the potential areas with medium and high gas production are mainly concentrated in the northern part of the study area, where lots of development research will be strengthened.

Geostress effect on resistivity and its relevant correction method

For reservoirs with abnormally high pressure and high geostress,formation resistivity can be greatly affected.This increase of resistivity resulting from high stress causes errors in the identification of reservoir fluids.In order to investigate the effect of stress on resistivity,resistivity measurement was conducted simultaneously with triaxial testing to obtain rock resistivity under high temperature and high pressure.The changes of resistivity and resistivity increasing coefficient with horizontal differential stress and minimum horizontal stress were revealed from experiments.Besides,field data were analyzed to show the main influencing factors of formation resistivity under reservoir conditions.In addition,a new resistivity correction model for high geostress formation was derived in this work.The interpretation results are in good agreement with well testing data in the Keshen area of the Tarim oilfield,China.