Temperature variation of the acoustical properties of laboratory sediments

Bell, David W.; Shirley, Donald J.

doi:10.1121/1.384627

Cited by 14 publications

(7 citation statements)

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“…7 Bell and Shirley measured the shear wave speeds in water-saturated sand with the grain size of 0.35 mm at the frequency of 7 kHz. The temperature dependence of the shear wave speed and attenuation depends on the grain size and the measuring frequency.…”

Section: B Results and Discussionmentioning

confidence: 99%

“…6 Measurements of the speed and attenuation of shear waves have been reported by many researchers. [7][8][9][10][11][12] The relationship of the shear wave speed to the mean grain size, porosity, or depth has been shown in their reports. However, they obtained most of their data at only a single frequency.…”

Section: Introductionmentioning

confidence: 99%

“…[7][8][9][10][11][12] Even in Brunson's data, the shear wave speed data are available at only one frequency, i.e., 10 kHz. 15 Therefore, it is very important to obtain shear wave speed dispersion data in order to perform a model-data comparison.…”

Section: Introductionmentioning

confidence: 99%

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Shear wave speed dispersion and attenuation in granular marine sediments

Kimura

2013

The Journal of the Acoustical Society of America

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The reported compressional wave speed dispersion and attenuation could be explained by a modified gap stiffness model incorporated into the Biot model (the BIMGS model). In contrast, shear wave speed dispersion and attenuation have not been investigated in detail. No measurements of shear wave speed dispersion have been reported, and only Brunson's data provide the frequency characteristics of shear wave attenuation. In this study, Brunson's attenuation measurements are compared to predictions using the Biot-Stoll model and the BIMGS model. It is shown that the BIMGS model accurately predicts the frequency dependence of shear wave attenuation. Then, the shear wave speed dispersion and attenuation in water-saturated silica sand are measured in the frequency range of 4-20 kHz. The vertical stress applied to the sample is 17.6 kPa. The temperature of the sample is set to be 5 °C, 20 °C, and 35 °C in order to change the relaxation frequency in the BIMGS model. The measured results are compared with those calculated using the Biot-Stoll model and the BIMGS model. It is shown that the shear wave speed dispersion and attenuation are predicted accurately by using the BIMGS model.

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Section: B Results and Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Shear wave speed dispersion and attenuation in granular marine sediments

Kimura

2013

The Journal of the Acoustical Society of America

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“…To make the estimation of clay-bound water (Phiclay*Vcl) even more difficult the petrophysical and acoustic properties of clay minerals vary with temperature (Bell and Shirley, 1980), pressure (Marion, Nur, and Han, 1992), and salinity. The author doesn't have a reference for the effects of salinity on petrophysical properties, but drilling studies show that the strength of shale in wells is affected by the salinity of the drilling mud.…”

Section: Comparing the Methodsmentioning

confidence: 99%

Using Wet Shale And Effective Porosity In A Petrophysical Velocity Model

May¹

2005

Offshore Technology Conference

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TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractIt is well known that sonic logs can be improved by using a petrophysical model to create a theoretical compressional and shear sonic. The measured sonic logs are only used as a guide. There are numerous techniques for doing this, although the most popular are the Xu, White and Keys model (Keys and Xu, Geophysics, 2002) and the Greenberg and Castangna method (Greenberg and Castangna, Geophysical Prospecting, 1992).These methods and most others require that the subject well be analyzed accurately for porosity, water saturation, and major lithologic and/or mineral components.Using the petrophysical analysis the compressional and shear moduli are built up step by step. First the moduli of the rock mixture are computed, then porosity is added to the mixture and finally the fluids are added using the Gassmann equation (Gassmann, F., Vierteljahrschrift der Naturforschenden Gesellschaft, 1951). The last step is to use the final Gassmann bulk and shear moduli to compute the compressional sonic log and the shear modulus to compute the shear sonic log. Sonic logs containing any fluid mixture can then be computed once this rock framework is built (Batzle and Wang, Geophysics, 1992).Past experience has shown us that measured sonic logs are subject to serious error due to borehole conditions and invasion. When the results of a petrophysical velocity model are used to compare wells to seismic or to build a rock strength model for pore pressure prediction or a well completion, the results are usually better than with the measured data alone.The best procedures for building these valuable models have yet to be agreed upon by the industry because the technology is still new. One of the debates is about how to add porosity and what porosity to use. Many petrophysicists prefer to use total porosity and dry clay volume to build their model. Others, like this author, prefer to use effective porosity and wet shale volume. The reasons behind this choice are presented.

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“…Density no longer plays a significant role, and the major factors become pressure, temperature, and frame rigidity. Bell and Shirley (1980) showed that the type of loose material makes no difference to the compressional wave (P-wave) velocity. Talwani et al (1973) showed that loose sediments exhibit hysteresis, that is, the velocity change with increasing pressure is reversible whereas the porosity change is not.…”

Section: Seismic Reflection Theorymentioning

confidence: 99%

The development of seismic reflection sandbox modeling

Sherlock

Evans

2001

Bulletin

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Analog sandbox models provide cheap, concise data and allow the evolution of geological structures to be observed under controlled laboratory conditions. Seismic physical modeling is used to study the effects of seismic wave propagation in isotropic and anisotropic media, and to improve methods of data acquisition, processing, and interpretation. By combining these two independent modeling techniques, the potential exists to expand the benefits of each method. For seismic physical modeling, the main advantages are that the seismic data collected from these models contain natural variations that cannot be built into conventional solid models, which are machined with predetermined structures. In addition, the cost and construction time to build these models is significantly reduced. For sandbox modeling, the ability to record threedimensional (3-D) seismic images before the model is manually sectioned for conventional two-dimensional (2-D) structural interpretation allows far more detailed study of subtle 3-D structures than previously possible. In the past other workers have attempted to use unconsolidated sands for seismic physical models, but these attempts have been unsuccessful because of the lack of control or understanding of the natural variations that occur throughout the models. The aim of our research has been to overcome such problems and to develop techniques to alter the acoustic impedance of sand layers, thereby allowing the subsequent ultrasonic seismic recording of 3-D fault systems in sand analog geological models.

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Temperature variation of the acoustical properties of laboratory sediments

Cited by 14 publications

References 0 publications

Shear wave speed dispersion and attenuation in granular marine sediments

Shear wave speed dispersion and attenuation in granular marine sediments

Using Wet Shale And Effective Porosity In A Petrophysical Velocity Model

The development of seismic reflection sandbox modeling

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