This article presents a case study concerning a seismic characterization project.Full-wave sonic logging was used to characterize the shallow compressional wave and shear wave velocity profiles in the site.Anomalous v...This article presents a case study concerning a seismic characterization project.Full-wave sonic logging was used to characterize the shallow compressional wave and shear wave velocity profiles in the site.Anomalous values of the Poisson’s ratio derived from the velocity profiles suggested that the boreholes might have traversed slow formations(i.e.with shear wave velocity smaller than the borehole fluid compressional wave velocity or“mud-wave speed”)and that conventional processing of the sonic logs might have misinterpreted the direct arrivals of fluid acoustic waves as arrivals caused by shear wave propagation in the rock.Consequently,the shear wave velocity profiles provided by the contractor were considered to be unreliable by the project team.To address these problems,a non-conventional determination of the shear wave velocity was implemented,based on the relationship between the Poisson’s ratio of the rock formation and the shape of the first train of sonic waves which arrived to the receivers in the sonic probe.The relationship was determined based on several hundreds of finite element simulations of the acoustic wave propagation in boreholes with the same diameter as used in the perforations.The present article describes how this non-conventional approach was developed and implemented to obtain the shear wave velocity profiles from the raw sonic logs.The approach allows an extension of the range of applicability of full-wave sonic logging to determination of shear wave velocity profiles in formations with low compressional wave velocities.The method could be used to obtain shear wave velocity profiles where compressional wave velocity is as low as slightly larger than the mud-wave speed.A sample sonic log in Log ASCII Standard(LAS)format is provided as supplementary material to this paper via Mendeley Data,together with the FORTRAN source code used to process the log following the approach described in this study.展开更多
It is still argued whether we measure phase or group velocities using acoustic logging tools. In this paper, three kinds of models are used to investigate this problem by theoretical analyses and numerical simulations...It is still argued whether we measure phase or group velocities using acoustic logging tools. In this paper, three kinds of models are used to investigate this problem by theoretical analyses and numerical simulations. First, we use the plane-wave superposition model containing two plane waves with different velocities and able to change the values of phase velocity and group velocity. The numerical results show that whether phase velocity is higher or lower than group velocity, using the slowness-time coherence （STC） method we can only get phase velocities. Second, according to the results of the dispersion analysis and branch-cut integration, in a rigid boundary borehole model the results of dispersion curves and the waveforms of the first-order mode show that the velocities obtained by the STC method are phase velocities while group velocities obtained by arrival time picking. Finally, dipole logging in a slow formation model is investigated using dispersion analysis and real-axis integration. The results of dispersion curves and full wave trains show similar conclusions as the borehole model with rigid boundary conditions.展开更多
A critical porosity model is often used to calculate the dry frame elastic modulus by the rock critical porosity value which is affected by many factors. In practice it is hard for us to obtain an accurate critical po...A critical porosity model is often used to calculate the dry frame elastic modulus by the rock critical porosity value which is affected by many factors. In practice it is hard for us to obtain an accurate critical porosity value and we can generally take only an empirical critical porosity value which often causes errors. In this paper, we propose a method to obtain the rock critical porosity value by inverting P-wave velocity and applying it to predict S-wave velocity. The applications of experiment and log data both show that the critical porosity inversion method can reduce the uncertainty resulting from using an empirical value in the past and provide the accurate critical porosity value for predicting S-wave velocity which significantly improves the prediction accuracy.展开更多
Shear wave velocity has numerous applications in geomechanical, petrophysical and geophysical studies of hydrocarbon reserves. However, data related to shear wave velocity isn’t available for all wells, especially ol...Shear wave velocity has numerous applications in geomechanical, petrophysical and geophysical studies of hydrocarbon reserves. However, data related to shear wave velocity isn’t available for all wells, especially old wells and it is very important to estimate this parameter using other well logging. Hence, lots of methods have been developed to estimate these data using other available information of reservoir. In this study, after processing and removing inappropriate petrophysical data, we estimated petrophysical properties affecting shear wave velocity of the reservoir and statistical methods were used to establish relationship between effective petrophysical properties and shear wave velocity. To predict (VS), first we used empirical relationships and then multivariate regression methods and neural networks were used. Multiple regression method is a powerful method that uses correlation between available information and desired parameter. Using this method, we can identify parameters affecting estimation of shear wave velocity. Neural networks can also be trained quickly and present a stable model for predicting shear wave velocity. For this reason, this method is known as “dynamic regression” compared with multiple regression. Neural network used in this study is not like a black box because we have used the results of multiple regression that can easily modify prediction of shear wave velocity through appropriate combination of data. The same information that was intended for multiple regression was used as input in neural networks, and shear wave velocity was obtained using compressional wave velocity and well logging data (neutron, density, gamma and deep resistivity) in carbonate rocks. The results show that methods applied in this carbonate reservoir was successful, so that shear wave velocity was predicted with about 92 and 95 percents of correlation coefficient in multiple regression and neural network method, respectively. Therefore, we propose using these methods to estimate shear wave velocity in wells without this parameter.展开更多
Transient S wave velocity rupture (TSVR) means the velocity of fault rupture propagation is between S wave velocity α and P wave velocity β . Its existing in the rupture of in plane ( i.e . strike slip...Transient S wave velocity rupture (TSVR) means the velocity of fault rupture propagation is between S wave velocity α and P wave velocity β . Its existing in the rupture of in plane ( i.e . strike slip) fault has been proved, but in 2 dimensional classical model, there are two difficulties in transient S wave velocity rupture, i.e ., initialization difficulty and divergence difficulty in interpreting the realization of TSVR. The initialization difficulty means, when v ↑ v R (Rayleigh wave velocity), the dynamic stress strength factor K 2(t) →+0, and changes from positive into negative in the interval ( v R, β ). How v transit the forbidden of ( v R, β )? The divergence difficulty means K 2(t) →+∞ when v ↓ β . Here we introduce the concept of fractal and tunnel effect that exist everywhere in fault. The structure of all the faults is fractal with multiple cracks. The velocity of fault rupture is differentiate of the length of the fault respect to time, so the rupture velocity is also fractal. The tunnel effect means the dynamic rupture crosses over the interval of the cracks, and the coalescence of the intervals is slower than the propagation of disturbance. Suppose the area of earthquake nucleation is critical or sub critical propagation everywhere, the arriving of disturbance triggers or accelerates the propagation of cracks tip at once, and the observation system cannot distinguish the front of disturbance and the tip of fracture. Then the speed of disturbance may be identified as fracture velocity, and the phenomenon of TSVR appears, which is an apparent velocity. The real reason of apparent velocity is that the mathematics model of shear rupture is simplified of complex process originally. The dual character of rupture velocity means that the apparent velocity of fault and the real velocity of micro crack extending, which are different in physics, but are unified in rupture criterion. Introducing the above mentioned concept to the calculation of K 2 (t) , the difficulty of initialization can be overcome, and the integral equation of triggering the initialization of TSVR is given quantitatively. By solving this integral equation, the lower limit of TSVR is 1.105 3 β , not β , and the divergence difficulty is overcome. TSVR is unstable solution, and may degenerate to sub Rayleigh wave velocity rupture immediately where the non critical condition can be measured. The results of this paper show that the initialization and continuum depends on the condition of earthquake nucleation in seismogenic area.展开更多
Based on S wave records of deep teleseisms on Digital Seismic Network of Shanxi Province, shear wave velocity structures beneath 6 stations were obtained by means of S wave waveform fitting. The result shows that the ...Based on S wave records of deep teleseisms on Digital Seismic Network of Shanxi Province, shear wave velocity structures beneath 6 stations were obtained by means of S wave waveform fitting. The result shows that the crust is thick in the studied region, reaching 40 km in thickness under 4 stations. The crust all alternatives high velocity layer with low velocity one. There appear varied velocity structures for different stations, and the stations around the same tectonic region exhibit similar structure characteristics. Combined with dominant depth distribution of many small-moderate earthquakes, the correlation between seismogenic layers and crustal structures of high and low velocity layers has been discussed.展开更多
Tengchong volcanic area is located near the impinging and underthrust margin of India and Eurasia plates. The volcanic activity is closely related to the tectonic environment. The deep structure characteristics are in...Tengchong volcanic area is located near the impinging and underthrust margin of India and Eurasia plates. The volcanic activity is closely related to the tectonic environment. The deep structure characteristics are inferred from the receiver function inversion with the teleseismic records in the paper. The results show that the low velocity zone is influenced by the NE-trending Dayingjiang fault. The S-wave low velocity structure occurs obviously in the southern part of the fault, but unobviously in its northern part. There are low velocity zones in the shallow po-sition, which coincides with the seismicity. It also demonstrates that the low velocity zone is directly related to the thermal activity in the volcanic area. Therefore, we consider that the volcano may be alive again.展开更多
This paper introduces horizon control, seismic control, logging control and facies control methods through the application of the least squares fitting of logging curves, seismic inversion and facies-controlled techni...This paper introduces horizon control, seismic control, logging control and facies control methods through the application of the least squares fitting of logging curves, seismic inversion and facies-controlled techniques. Based on the microgeology and thin section analyses, the lithology, lithofacies and periods of the Permian igneous rocks are described in detail. The seismic inversion and facies-controlled techniques were used to find the distribution characteristics of the igneous rocks and the 3D velocity volume. The least squares fitting of the logging curves overcome the problem that the work area is short of density logging data. Through analysis of thin sections, the lithofacies can be classified into eruption airfall subfacies, eruption pyroclastic flow subfacies and eruption facies.展开更多
Using pure S wave fitting method, we studied the shear wave velocity structures under the Ordos block and its eastern and southern marginal areas. The results show that the velocity structure beneath Yulin station in ...Using pure S wave fitting method, we studied the shear wave velocity structures under the Ordos block and its eastern and southern marginal areas. The results show that the velocity structure beneath Yulin station in the interior of Ordos block is relatively stable, where no apparent change between high and low velocity layers exists and the shear wave velocity increases steadily with the depth. There is a 12km thick layer at the depth of 25km under this station, with an S wave velocity (V S=3.90km/s) lower than that at the same depth in its eastern and southern areas (V S≥4.00km/s). The crust under the eastern margin of Ordos block is thicker than that of the Yulin station, and the velocity structures alternate between the high and low velocity layers, with more low velocity layers. It has the same characteristic as having a 10km-thick low velocity layer (V S=3.80km/s) in the lower crust but buried at a depth of about 35km. Moreover, we studied the V P/V S ratio under each station in combination with the result of P wave velocity inversion. The results show that, the average velocity ratio of the Yulin station at the interior of Ordos block is only 1.68, with a very low ratio (about 1.60) in the upper crust and a stable ratio of about 1.73 in the mid and lower crust, which indicates the media under this station is homogenous and stable, being in a state of rigidity. But at the stations in the eastern and southern margins of the Ordos block, several layers of high velocity ratio (about 1.80) have been found, in which the average velocity ratio under Kelan and Lishi stations at the eastern margin is systemically higher than that of the general elastical body waves (1.732). This reflects that the crust under the marginal areas is more active relatively, and other materials may exist in these layers. Finally, we discussed the relationship among earthquakes, velocity structures beneath stations and faults.展开更多
In this study,on the basis of absolute first-arrival times of 84756 P-and S-waves from 6085 earthquakes recorded at 56 fixed stations in Yibin and surrounding areas in China from January 2009 to January 2019,focal par...In this study,on the basis of absolute first-arrival times of 84756 P-and S-waves from 6085 earthquakes recorded at 56 fixed stations in Yibin and surrounding areas in China from January 2009 to January 2019,focal parameters and three-dimensional(3 D)body-wave high-resolution velocity structures at depths of 0–30 km were retrieved by double-difference tomography.Results show that there is a good correspondence between the spatial distribution of the relocated earthquakes and velocity structures,which were concentrated mainly in the high-velocity-anomaly region or edge of high-velocity region.Velocity structure of P-and S-waves in the Yibin area clearly shows lateral inhomogeneity.The distribution characteristics of the P-and S-waves near the surface are closely related to the geomorphology and geologic structure.The low-velocity anomaly appears at the depth of 15–25 km,which is affected by the lower crust current.The Junlian–Gongxian and Gongxian–Changning earthquake areas,which are the two most earthquake-prone areas in the Yibin region,clearly differ in earthquake distribution and tectonic characteristics.We analyzed the structural characteristics of the Junlian–Gongxian and Gongxian–Changning earthquake areas on the basis of the 3 D bodywave velocity structures in the Yibin region.We found that although most seismicity in the Yibin area is caused by fluid injection,the spatial position of seismicity is controlled by the velocity structures of the middle and upper crust and local geologic structure.Fine-scale 3 D velocity structures in the Yibin area provide important local reference information for further understanding the crustal medium,seismogenic structure,and seismicity.展开更多
文摘This article presents a case study concerning a seismic characterization project.Full-wave sonic logging was used to characterize the shallow compressional wave and shear wave velocity profiles in the site.Anomalous values of the Poisson’s ratio derived from the velocity profiles suggested that the boreholes might have traversed slow formations(i.e.with shear wave velocity smaller than the borehole fluid compressional wave velocity or“mud-wave speed”)and that conventional processing of the sonic logs might have misinterpreted the direct arrivals of fluid acoustic waves as arrivals caused by shear wave propagation in the rock.Consequently,the shear wave velocity profiles provided by the contractor were considered to be unreliable by the project team.To address these problems,a non-conventional determination of the shear wave velocity was implemented,based on the relationship between the Poisson’s ratio of the rock formation and the shape of the first train of sonic waves which arrived to the receivers in the sonic probe.The relationship was determined based on several hundreds of finite element simulations of the acoustic wave propagation in boreholes with the same diameter as used in the perforations.The present article describes how this non-conventional approach was developed and implemented to obtain the shear wave velocity profiles from the raw sonic logs.The approach allows an extension of the range of applicability of full-wave sonic logging to determination of shear wave velocity profiles in formations with low compressional wave velocities.The method could be used to obtain shear wave velocity profiles where compressional wave velocity is as low as slightly larger than the mud-wave speed.A sample sonic log in Log ASCII Standard(LAS)format is provided as supplementary material to this paper via Mendeley Data,together with the FORTRAN source code used to process the log following the approach described in this study.
基金supported by the National Natural Science Foundation of China (Grant No. 40774099, 10874202 and 11134011)National 863 Program of China (Grant No. 2008AA06Z205)
文摘It is still argued whether we measure phase or group velocities using acoustic logging tools. In this paper, three kinds of models are used to investigate this problem by theoretical analyses and numerical simulations. First, we use the plane-wave superposition model containing two plane waves with different velocities and able to change the values of phase velocity and group velocity. The numerical results show that whether phase velocity is higher or lower than group velocity, using the slowness-time coherence （STC） method we can only get phase velocities. Second, according to the results of the dispersion analysis and branch-cut integration, in a rigid boundary borehole model the results of dispersion curves and the waveforms of the first-order mode show that the velocities obtained by the STC method are phase velocities while group velocities obtained by arrival time picking. Finally, dipole logging in a slow formation model is investigated using dispersion analysis and real-axis integration. The results of dispersion curves and full wave trains show similar conclusions as the borehole model with rigid boundary conditions.
基金sponsored by Important National Science and Technology Specifi c Projects of China (No.2011ZX05001)
文摘A critical porosity model is often used to calculate the dry frame elastic modulus by the rock critical porosity value which is affected by many factors. In practice it is hard for us to obtain an accurate critical porosity value and we can generally take only an empirical critical porosity value which often causes errors. In this paper, we propose a method to obtain the rock critical porosity value by inverting P-wave velocity and applying it to predict S-wave velocity. The applications of experiment and log data both show that the critical porosity inversion method can reduce the uncertainty resulting from using an empirical value in the past and provide the accurate critical porosity value for predicting S-wave velocity which significantly improves the prediction accuracy.
文摘Shear wave velocity has numerous applications in geomechanical, petrophysical and geophysical studies of hydrocarbon reserves. However, data related to shear wave velocity isn’t available for all wells, especially old wells and it is very important to estimate this parameter using other well logging. Hence, lots of methods have been developed to estimate these data using other available information of reservoir. In this study, after processing and removing inappropriate petrophysical data, we estimated petrophysical properties affecting shear wave velocity of the reservoir and statistical methods were used to establish relationship between effective petrophysical properties and shear wave velocity. To predict (VS), first we used empirical relationships and then multivariate regression methods and neural networks were used. Multiple regression method is a powerful method that uses correlation between available information and desired parameter. Using this method, we can identify parameters affecting estimation of shear wave velocity. Neural networks can also be trained quickly and present a stable model for predicting shear wave velocity. For this reason, this method is known as “dynamic regression” compared with multiple regression. Neural network used in this study is not like a black box because we have used the results of multiple regression that can easily modify prediction of shear wave velocity through appropriate combination of data. The same information that was intended for multiple regression was used as input in neural networks, and shear wave velocity was obtained using compressional wave velocity and well logging data (neutron, density, gamma and deep resistivity) in carbonate rocks. The results show that methods applied in this carbonate reservoir was successful, so that shear wave velocity was predicted with about 92 and 95 percents of correlation coefficient in multiple regression and neural network method, respectively. Therefore, we propose using these methods to estimate shear wave velocity in wells without this parameter.
文摘Transient S wave velocity rupture (TSVR) means the velocity of fault rupture propagation is between S wave velocity α and P wave velocity β . Its existing in the rupture of in plane ( i.e . strike slip) fault has been proved, but in 2 dimensional classical model, there are two difficulties in transient S wave velocity rupture, i.e ., initialization difficulty and divergence difficulty in interpreting the realization of TSVR. The initialization difficulty means, when v ↑ v R (Rayleigh wave velocity), the dynamic stress strength factor K 2(t) →+0, and changes from positive into negative in the interval ( v R, β ). How v transit the forbidden of ( v R, β )? The divergence difficulty means K 2(t) →+∞ when v ↓ β . Here we introduce the concept of fractal and tunnel effect that exist everywhere in fault. The structure of all the faults is fractal with multiple cracks. The velocity of fault rupture is differentiate of the length of the fault respect to time, so the rupture velocity is also fractal. The tunnel effect means the dynamic rupture crosses over the interval of the cracks, and the coalescence of the intervals is slower than the propagation of disturbance. Suppose the area of earthquake nucleation is critical or sub critical propagation everywhere, the arriving of disturbance triggers or accelerates the propagation of cracks tip at once, and the observation system cannot distinguish the front of disturbance and the tip of fracture. Then the speed of disturbance may be identified as fracture velocity, and the phenomenon of TSVR appears, which is an apparent velocity. The real reason of apparent velocity is that the mathematics model of shear rupture is simplified of complex process originally. The dual character of rupture velocity means that the apparent velocity of fault and the real velocity of micro crack extending, which are different in physics, but are unified in rupture criterion. Introducing the above mentioned concept to the calculation of K 2 (t) , the difficulty of initialization can be overcome, and the integral equation of triggering the initialization of TSVR is given quantitatively. By solving this integral equation, the lower limit of TSVR is 1.105 3 β , not β , and the divergence difficulty is overcome. TSVR is unstable solution, and may degenerate to sub Rayleigh wave velocity rupture immediately where the non critical condition can be measured. The results of this paper show that the initialization and continuum depends on the condition of earthquake nucleation in seismogenic area.
基金funded by the National Natural Science Foundation of China (grant no.42074149)the Natural Science Foundation of Jiangsu Province (grant no.BK20201318)。
基金State Key Basic Development and Programming Project Mechanism and Prediction of Continental Strong Earthquakes (G1998040705).
文摘Based on S wave records of deep teleseisms on Digital Seismic Network of Shanxi Province, shear wave velocity structures beneath 6 stations were obtained by means of S wave waveform fitting. The result shows that the crust is thick in the studied region, reaching 40 km in thickness under 4 stations. The crust all alternatives high velocity layer with low velocity one. There appear varied velocity structures for different stations, and the stations around the same tectonic region exhibit similar structure characteristics. Combined with dominant depth distribution of many small-moderate earthquakes, the correlation between seismogenic layers and crustal structures of high and low velocity layers has been discussed.
文摘Tengchong volcanic area is located near the impinging and underthrust margin of India and Eurasia plates. The volcanic activity is closely related to the tectonic environment. The deep structure characteristics are inferred from the receiver function inversion with the teleseismic records in the paper. The results show that the low velocity zone is influenced by the NE-trending Dayingjiang fault. The S-wave low velocity structure occurs obviously in the southern part of the fault, but unobviously in its northern part. There are low velocity zones in the shallow po-sition, which coincides with the seismicity. It also demonstrates that the low velocity zone is directly related to the thermal activity in the volcanic area. Therefore, we consider that the volcano may be alive again.
基金A Project Funded by National Science and Technology Major Project (2011ZX05001-002-003)the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD)Key Laboratory for Coalbed Methane Resources and Reservoir formation Process, CUMT, Ministry of Education, China
文摘This paper introduces horizon control, seismic control, logging control and facies control methods through the application of the least squares fitting of logging curves, seismic inversion and facies-controlled techniques. Based on the microgeology and thin section analyses, the lithology, lithofacies and periods of the Permian igneous rocks are described in detail. The seismic inversion and facies-controlled techniques were used to find the distribution characteristics of the igneous rocks and the 3D velocity volume. The least squares fitting of the logging curves overcome the problem that the work area is short of density logging data. Through analysis of thin sections, the lithofacies can be classified into eruption airfall subfacies, eruption pyroclastic flow subfacies and eruption facies.
文摘Using pure S wave fitting method, we studied the shear wave velocity structures under the Ordos block and its eastern and southern marginal areas. The results show that the velocity structure beneath Yulin station in the interior of Ordos block is relatively stable, where no apparent change between high and low velocity layers exists and the shear wave velocity increases steadily with the depth. There is a 12km thick layer at the depth of 25km under this station, with an S wave velocity (V S=3.90km/s) lower than that at the same depth in its eastern and southern areas (V S≥4.00km/s). The crust under the eastern margin of Ordos block is thicker than that of the Yulin station, and the velocity structures alternate between the high and low velocity layers, with more low velocity layers. It has the same characteristic as having a 10km-thick low velocity layer (V S=3.80km/s) in the lower crust but buried at a depth of about 35km. Moreover, we studied the V P/V S ratio under each station in combination with the result of P wave velocity inversion. The results show that, the average velocity ratio of the Yulin station at the interior of Ordos block is only 1.68, with a very low ratio (about 1.60) in the upper crust and a stable ratio of about 1.73 in the mid and lower crust, which indicates the media under this station is homogenous and stable, being in a state of rigidity. But at the stations in the eastern and southern margins of the Ordos block, several layers of high velocity ratio (about 1.80) have been found, in which the average velocity ratio under Kelan and Lishi stations at the eastern margin is systemically higher than that of the general elastical body waves (1.732). This reflects that the crust under the marginal areas is more active relatively, and other materials may exist in these layers. Finally, we discussed the relationship among earthquakes, velocity structures beneath stations and faults.
基金supported by the Research Project of Tianjin Earthquake Agency(No.yb201901)Seismic Regime Tracking Project of CEA(No.2019010127)Combination Project with Monitoring,Prediction and Scientific Research of Earthquake Technology,CEA(No.3JH-201901006)
文摘In this study,on the basis of absolute first-arrival times of 84756 P-and S-waves from 6085 earthquakes recorded at 56 fixed stations in Yibin and surrounding areas in China from January 2009 to January 2019,focal parameters and three-dimensional(3 D)body-wave high-resolution velocity structures at depths of 0–30 km were retrieved by double-difference tomography.Results show that there is a good correspondence between the spatial distribution of the relocated earthquakes and velocity structures,which were concentrated mainly in the high-velocity-anomaly region or edge of high-velocity region.Velocity structure of P-and S-waves in the Yibin area clearly shows lateral inhomogeneity.The distribution characteristics of the P-and S-waves near the surface are closely related to the geomorphology and geologic structure.The low-velocity anomaly appears at the depth of 15–25 km,which is affected by the lower crust current.The Junlian–Gongxian and Gongxian–Changning earthquake areas,which are the two most earthquake-prone areas in the Yibin region,clearly differ in earthquake distribution and tectonic characteristics.We analyzed the structural characteristics of the Junlian–Gongxian and Gongxian–Changning earthquake areas on the basis of the 3 D bodywave velocity structures in the Yibin region.We found that although most seismicity in the Yibin area is caused by fluid injection,the spatial position of seismicity is controlled by the velocity structures of the middle and upper crust and local geologic structure.Fine-scale 3 D velocity structures in the Yibin area provide important local reference information for further understanding the crustal medium,seismogenic structure,and seismicity.
