A new velocity model for clay-sand mixtures1

None of the standard porosity-velocity models (e.g. the time-average equation, Raymer's equations) is satisfactory for interpreting well-logging data over a broad depth range. Clays in the section are the usual source of the difficulty through the bias and scatter that they introduce into the relationship between porosity and P-wave transit time. Because clays are composed of fine sheet-like particles, they normally form pores with much smaller aspect ratios than those associated with sand grains. This difference in pore geometry provides the key to obtaining more consistent resistivity and sonic log interpretations. A velocity model for Clay–sand mixtures has been developed in terms of the Kuster and Toksöz, effective medium and Gassmann theories. In this model, the total pore space is assumed to consist of two parts: (1) pores associated with sand grains and (2) pores associated with clays (including bound water). The essential feature of the model is the assumption that the geometry of pores associated with sand grains is significantly different from that associated with clays. Because of this, porosity in shales affects elastic compliance differently from porosity in sand-Stones. The predictive power of the model is demonstrated by the agreement between its predictions and laboratory measurements and by its ability to predict sonic logs from other logs over large depth intervals where formations vary from unconsolidated to consolidated sandstones and shales.     

Shear wave velocity prediction during CO<Subscript>2</Subscript>-EOR and sequestration in the Gao89 well block of the Shengli Oilfield

Shear-wave velocity is a key parameter for calibrating monitoring time-lapse 4D seismic data during CO₂-EOR (Enhanced Oil Recovery) and CO₂ sequestration. However, actual S-wave velocity data are lacking, especially in 4D data for CO₂ sequestration because wells are closed after the CO₂ injection and seismic monitoring is continued but no well log data are acquired. When CO₂ is injected into a reservoir, the pressure and saturation of the reservoirs change as well as the elastic parameters of the reservoir rocks. We propose a method to predict the S-wave velocity in reservoirs at different pressures and porosities based on the Hertz–Mindlin and Gassmann equations. Because the coordination number is unknown in the Hertz–Mindlin equation, we propose a new method to predict it. Thus, we use data at different CO₂ injection stages in the Gao89 well block, Shengli Oilfield. First, the sand and mud beds are separated based on the structural characteristics of the thin sand beds and then the S-wave velocity as a function of reservoir pressure and porosity is calculated. Finally, synthetic seismic seismograms are generated based on the predicted P- and S-wave velocities at different stages of CO₂ injection.     

Constraints on velocity-depth trends from rock physics models

Estimates of depth, overpressure and amount of exhumation based on sonic data for a sedimentary formation rely on identification of a normal velocity–depth trend for the formation. Such trends describe how sonic velocity increases with depth in relatively homogeneous, brine‐saturated sedimentary formations as porosity is reduced during normal compaction (mechanical and chemical). Compaction is ‘normal’ when the fluid pressure is hydrostatic and the thickness of the overburden has not been reduced by exhumation. We suggest that normal porosity at the surface for a given lithology should be constrained by its critical porosity, i.e. the porosity limit above which a particular sediment exists only as a suspension. Consequently, normal velocity at the surface of unconsolidated sediments saturated with brine approaches the velocity of the sediment in suspension. Furthermore, porosity must approach zero at infinite depth, so the velocity approaches the matrix velocity of the rock and the velocity–depth gradient approaches zero. For sediments with initially good grain contact (when porosity is just below the critical porosity), the velocity gradient decreases with depth. By contrast, initially compliant sediments may have a maximum velocity gradient at some depth if we assume that porosity decreases exponentially with depth. We have used published velocity–porosity–depth relationships to formulate normal velocity–depth trends for consolidated sandstone with varying clay content and for marine shale dominated by smectite/illite. The first relationship is based on a modified Voigt trend (porosity scaled by critical porosity) and the second is based on a modified time‐average equation. Baselines for sandstone and shale in the North Sea agree with the established constraints and the shale trend can be applied to predict overpressure. A normal velocity–depth trend for a formation cannot be expressed from an arbitrary choice of mathematical functions and regression parameters, but should be considered as a physical model linked to the velocity–porosity transforms developed in rock physics.     

A semi-empirical approach to model pressure dependence of elastic moduli in granular media accounting for variations of coordination-number and Poisson-ratio

The effective medium theory based on the Hertz–Mindlin contact law is the most popular theory to relate dynamic elastic moduli (or elastic velocities) and confining pressure in dry granular media. However, many experimental results proved that the effective medium theory predicts pressure trends lower than experimental ones and over-predicts the shear modulus. To mitigate these mispredictions, several evolutions of the effective medium theory have been presented in the literature. Among these, the model named modified grain contact theory is an empirical approach in which three parametric curves are included in the effective medium theory model. Fitting the parameters of these curves permits to adjust the pressure trends of the Poisson ratio and the bulk modulus. In this paper, we present two variations of the modified grain contact theory model. First, we propose a minor modification in the fitting function for the porosity dependence of the calibration parameters that accounts for non-linearity in the vicinity of the critical porosity. Second, we propose a major modification that reduces the three-step modified grain contact theory model to a two-step model, by skipping the calibration parameter–porosity fit in the model and directly modelling the calibration parameter–pressure relation. In addition to an increased simplicity (the fitting parameters are reduced from 10 to 6), avoiding the porosity fit permits us to apply the model to laboratory data that are not provided with accurate porosity measurements. For this second model, we also estimate the uncertainty of the fitting parameters and the elastic velocities. We tested this model on dry core measurements from literature and we verified that it returns elastic velocity trends as good as the original modified grain contact theory model with a reduced number of fitting parameters. Possible developments of the new model to add predictive power are also discussed.     

Mechanical compaction and ultrasonic velocity of sands with different texture and mineralogical composition

This study presents the results of experimental compaction while measuring ultrasonic velocities of sands with different grain size, shape, sorting and mineralogy. Uniaxial mechanical compaction tests up to a maximum of 50 MPa effective stress were performed on 29 dry sand aggregates derived from eight different sands to measure the rock properties. A good agreement was found between the Gassmann saturated bulk moduli of dry and brine saturated tests of selected sands. Sand samples with poor sorting showed low initial porosity while sands with high grain angularity had high initial porosity. The sand compaction tests showed that at a given stress well‐sorted, coarse‐grained sands were more compressible and had higher velocities (Vp and Vs) than fine‐grained sands when the mineralogy was similar. This can be attributed to grain crushing, where coarser grains lead to high compressibility and large grain‐to‐grain contact areas result in high velocities. At medium to high stresses the angular coarse to medium grained sands (both sorted sands and un‐sorted whole sands) showed high compaction and velocities (Vp and Vs). The small grain‐to‐grain contact areas promote higher deformation at grain contacts, more crushing and increased porosity loss resulting in high velocities. Compaction and velocities (Vp and Vs) increased with decreasing sorting in sands. However, at the same porosity, the velocities in whole sands were slightly lower than in the well‐sorted sands indicating the presence of loose smaller grains in‐between the framework grains. Quartz‐poor sands (containing less than 55% quartz) showed higher velocities (Vp and Vs) compared to that of quartz‐rich sands. This could be the result of sintering and enlargement of grain contacts of ductile mineral grains in the quartz‐poor sands increasing the effective bulk and shear stiffness. Tests both from wet measurements and Gassmann brine substitution showed a decreasing Vp/Vs ratio with increasing effective stress. The quartz‐rich sands separated out towards the higher side of the Vp/Vs range. The Gassmann brine substituted Vp and Vs plotted against effective stress provide a measure of the expected velocity range to be found in these and similar sands during mechanical compaction. Deviations of actual well log data from experimental data may indicate uplift, the presence of hydrocarbon, overpressure and/or cementation. Data from this study may help to model velocity‐depth trends and to improve the characterization of reservoir sands from well log data in a low temperature (<80–100^o C) zone where compaction of sands is mostly mechanical.     

Acoustic and petrophysical properties of mechanically compacted overconsolidated sands: Part 2 – Rock physics modelling and applications

Part one of this paper reported results from experimental compaction measurements of unconsolidated natural sand samples with different mineralogical compositions and textures. The experimental setup was designed with several cycles of stress loading and unloading applied to the samples. The setup was aimed to simulate a stress condition where sediments underwent episodes of compaction, uplift and erosion. P-wave and S-wave velocities and corresponding petrophysical (porosity and density) properties were reported. In this second part of the paper, rock physics modelling utilizing existing rock physics models to evaluate the model validity for measured data from part one were presented. The results show that a friable sand model, which was established for normally compacted sediments is also capable of describing overconsolidated sediments. The velocity–porosity data plotted along the friable sand lines not only describe sorting deterioration, as has been traditionally explained by other studies, but also variations in pre-consolidation stress or degree of stress release. The deviation of the overconsolidated sands away from the normal compaction trend on the V_P/V_S and acoustic impedance space shows that various stress paths can be predicted on this domain when utilizing rock physics templates. Fluid saturation sensitivity is found to be lower in overconsolidated sands compared to normally consolidated sands. The sensitivity decreases with increasing pre-consolidation stress. This means detectability for four-dimensional fluid saturation changes can be affected if sediments were pre-stressed and unloaded. Well log data from the Barents Sea show similar patterns to the experimental sand data. The findings allow the development of better rock physics diagnostics of unloaded sediments, and the understanding of expected 4D seismic response during time-lapse seismic monitoring of uplifted basins. The studied outcomes also reveal an insight into the friable sand model that its diagnostic value is not only for describing sorting microtextures, but also pre-consolidation stress history. The outcome extends the model application for pre-consolidation stress estimation, for any unconsolidated sands experiencing similar unloading stress conditions to this study.     

Modelling elastic properties of impure chalk from South Arne Field, North Sea

In impure chalk, the elastic moduli are not only controlled by porosity but also by contact‐cementation, resulting in relatively large moduli for a given porosity, and by admixtures of clay and fine silica, which results in relatively small moduli for a given porosity. Based on a concept of solids suspended in pore fluids as well as composing the rock frame, we model P‐wave and S‐wave moduli of dry and wet plug samples by an effective‐medium Hashin–Shtrikman model, using chemical, mineralogical and textural input. For a given porosity, the elastic moduli correspond to a part of the solid (the iso‐frame value) forming the frame of an Upper Hashin–Shtrikman bound, whereas the remaining solid is modelled as suspended in the pore fluid. The iso‐frame model is thus a measure of the pore‐stiffness or degree of cementation of the chalk. The textural and mineralogical data may be assessed from logging data on spectral gamma radiation, density, sonic velocity and water saturation in a hydrocarbon zone, whereas the iso‐frame value of a chalk may be assessed from the density and acoustic P‐wave logs alone. The iso‐frame concept may thus be directly used in conventional log‐analysis and is a way of incorporating sonic‐logging data. The Rigs‐1 and Rigs‐2 wells in the South Arne field penetrate the chalk at the same depth but differ in porosity and in water saturation although almost the entire chalk interval has irreducible water saturation. Our model, combined with petrographic data, indicates that the difference in porosity is caused by a higher degree of pore‐filling cementation in Rigs‐1. Petrographic data indicate that the difference in water saturation is caused by a higher content of smectite in the pores of Rigs‐1. In both wells, we find submicron‐size diagenetic quartz.     

部分饱和砂岩储层地震物理模拟及含气饱和度预测分析

含气饱和度预测是天然气储层地震解释工作的重要目标.本文将岩石物理分析与地震物理模拟技术相结合,构建了部分;饱和砂岩储层物理模型并进行含气饱和度预测分析.物理模型中设置了高孔渗常规砂岩和低孑孔渗致密砂岩两种模拟储层,每种储层都是由具有不同含水饱和度的气-水双相饱和砂体组成.岩石物理分析结果显示在低孔渗致密砂岩中气-水混合流体更加倾向于非均匀的斑块分布,而结合了Brie等效流体公式的Gassmann流体替换理论可以更准确地描述纵波速度随含水饱和度的变化趋势.对物理模型进行地震资料采集处理后,对比了AVO特征和叠前同步反演结果对两种砂岩储层含气饱和度预测能力的差异.AVO特征结果显示,对于混合流体均匀分布的高孔渗砂岩储层,AVO响应曲线和属性变化很难对含气饱和度进行估算;对于混合流体斑块分布的致密砂岩储层,AVO特征可以定性地分辨出储层是否为高、中、低含气情况.反演结果显示,密度及纵横波速度比分别对高孔渗及致密砂岩储层的含气饱和度有着较好的指示能力.     

SHEAR-WAVE VELOCITY ESTIMATION IN POROUS ROCKS: THEORETICAL FORMULATION,PRELIMINARY VERIFICATION AND APPLICATIONS1

Shear-wave velocity logs are useful for various seismic interpretation applications, including bright spot analyses, amplitude-versus-offset analyses and multicomponent seismic interpretations. Measured shear-wave velocity logs are, however, often unavailable. We developed a general method to predict shear-wave velocity in porous rocks. If reliable compressional-wave velocity, lithology, porosity and water saturation data are available, the precision and accuracy of shear-wave velocity prediction are 9% and 3%, respectively. The success of our method depends on: (1) robust relationships between compressional- and shear-wave velocities for water-saturated, pure, porous lithologies; (2) nearly linear mixing laws for solid rock constituents; (3) first-order applicability of the Biot–Gassmann theory to real rocks. We verified these concepts with laboratory measurements and full waveform sonic logs. Shear-wave velocities estimated by our method can improve formation evaluation. Our method has been successfully tested with data from several locations.     

A physical model for shear-wave velocity prediction1

The clay-sand mixture model of Xu and White is shown to simulate observed relationships between S-wave velocity (or transit time), porosity and clay content. In general, neither S-wave velocity nor S-wave transit time is a linear function of porosity and clay content. For practical purposes, clay content is approximated by shale volume in well-log applications. In principle, the model can predict S-wave velocity from lithology and any pair of P-wave velocity, porosity and shale volume. Although the predictions should be the same if all measurements are error free, comparison of predictions with laboratory and logging measurements show that predictions using P-wave velocity are the most reliable. The robust relationship between S- and P-wave velocities is due to the fact that both are similarly affected by porosity, clay content and lithology. Moreover, errors in the measured P-wave velocity are normally smaller than those in porosity and shale volume, both of which are subject to errors introduced by imperfect models and imperfect parameters when estimated from logs. Because the model evaluates the bulk and shear moduli of the dry rock frame by a combination of Kuster and Toksöz’ theory and differential effective medium theory, using pore aspect ratios to characterize the compliances of the sand and clay components, the relationship between P- and S-wave velocities is explicit and consistent. Consequently the model sidesteps problems and assumptions that arise from the lack of knowledge of these moduli when applying Gassmann's theory to this relationship, making it a very flexible tool for investigating how the v_P-v_s relationship is affected by lithology, porosity, clay content and water saturation. Numerical results from the model are confirmed by laboratory and logging data and demonstrate, for example, how the presence of gas has a more pronounced effect on P-wave velocity in shaly sands than in less compliant cleaner sandstones.     

模拟天然气水合物的岩石物理特性模型实验

针对水合物沉积的悬浮、颗粒接触和胶结三种微观模式,制作一组微弱胶结非固结高孔隙度人造样品和颗粒填充渐变的三维物理模型. 通过物理模型实验研究天然气水合物物性参数的敏感性. 实验结果表明：在弱颗粒间胶结物和低有效应力的固结差的沉积物中,声波对孔隙流体性质较敏感. 随着温度的降低颗粒胶结,改变原有沉积物的岩石物理特性,速度、弹性模量和频率升高,声波衰减和Vp/VS减小,沉积层内的反射波消隐.     

Committee neural networks for porosity and permeability prediction from well logs

Neural computing has moved beyond simple demonstration to more significant applications. Encouraged by recent developments in artificial neural network (ANN) modelling techniques, we have developed committee machine (CM) networks for converting well logs to porosity and permeability, and have applied the networks to real well data from the North Sea. Simple three‐layer back‐propagation ANNs constitute the blocks of a modular system where the porosity ANN uses sonic, density and resistivity logs for input. The permeability ANN is slightly more complex, with four inputs (density, gamma ray, neutron porosity and sonic). The optimum size of the hidden layer, the number of training data required, and alternative training techniques have been investigated using synthetic logs. For both networks an optimal number of neurons in the hidden layer is in the range 8–10. With a lower number of hidden units the network fails to represent the problem, and for higher complexity overfitting becomes a problem when data are noisy. A sufficient number of training samples for the porosity ANN is around 150, while the permeability ANN requires twice as many in order to keep network errors well below the errors in core data. For the porosity ANN the overtraining strategy is the suitable technique for bias reduction and an unconstrained optimal linear combination (OLC) is the best method of combining the CM output. For permeability, on the other hand, the combination of overtraining and OLC does not work. Error reduction by validation, simple averaging combined with range‐splitting provides the required accuracy. The accuracy of the resulting CM is restricted only by the accuracy of the real data. The ANN approach is shown to be superior to multiple linear regression techniques even with minor non‐linearity in the background model.     

Using wavelet‐domain adaptive filtering to improve signal‐to‐noise ratio of nuclear magnetic resonance log data from tight gas sands

In tight gas sands, the signal‐to‐noise ratio of nuclear magnetic resonance log data is usually low, which limits the application of nuclear magnetic resonance logs in this type of reservoir. This project uses the method of wavelet‐domain adaptive filtering to denoise the nuclear magnetic resonance log data from tight gas sands. The principles of the maximum correlation coefficient and the minimum root mean square error are used to decide on the optimal basis function for wavelet transformation. The feasibility and the effectiveness of this method are verified by analysing the numerical simulation results and core experimental data. Compared with the wavelet thresholding denoise method, this adaptive filtering method is more effective in noise filtering, which can improve the signal‐to‐noise ratio of nuclear magnetic resonance data and the inversion precision of transverse relaxation time T₂ spectrum. The application of this method to nuclear magnetic resonance logs shows that this method not only can improve the accuracy of nuclear magnetic resonance porosity but also can enhance the recognition ability of tight gas sands in nuclear magnetic resonance logs.     

A semi-empirical velocity-porosity-clay model for petrophysical interpretation of P- and S-velocities

We design a velocity–porosity model for sand-shale environments with the emphasis on its application to petrophysical interpretation of compressional and shear velocities. In order to achieve this objective, we extend the velocity–porosity model proposed by Krief et al., to account for the effect of clay content in sandstones, using the published laboratory experiments on rocks and well log data in a wide range of porosities and clay contents. The model of Krief et al. works well for clean compacted rocks. It assumes that compressional and shear velocities in a porous fluid-saturated rock obey Gassmann formulae with the Biot compliance coefficient. In order to use this model for clay-rich rocks, we assume that the bulk and shear moduli of the grain material, and the dependence of the compliance on porosity, are functions of the clay content. Statistical analysis of published laboratory data shows that the moduli of the matrix grain material are best defined by low Hashin–Shtrikman bounds. The parameters of the model include the bulk and shear moduli of the sand and clay mineral components as well as coefficients which define the dependence of the bulk and shear compliance on porosity and clay content. The constants of the model are determined by a multivariate non-linear regression fit for P- and S-velocities as functions of porosity and clay content using the data acquired in the area of interest. In order to demonstrate the potential application of the proposed model to petrophysical interpretation, we design an inversion procedure, which allows us to estimate porosity, saturation and/or clay content from compressional and shear velocities. Testing of the model on laboratory data and a set of well logs from Carnarvon Basin, Australia, shows good agreement between predictions and measurements. This simple velocity-porosity-clay semi-empirical model could be used for more reliable petrophysical interpretation of compressional and shear velocities obtained from well logs or surface seismic data.     

Well tie,fluid substitution and AVO modelling: a North Sea example

Accurate well ties are essential to practical seismic lithological interpretation. As long as the geology in the vicinity of the reservoir is not unduly complex, the main factors controlling this accuracy are the processing of the seismic data and the construction of the seismic model from well logs. This case study illustrates how seismic data processing to a near-offset stack, quality control of logs and petrophysical modelling improved a well tie at an oil reservoir. We demonstrate the application of a predictive petrophysical model in the preparation and integration of the logs before building the seismic model and we quantify our improvements in well-tie accuracy. The data for the study consisted of seismic field data from a 3D sail line through a well in a North Sea oilfield and a suite of standard logs at the well. A swathe of fully processed 3D data through the well was available for comparison. The well tie in the shallow section from first-pass seismic data processing and a routinely edited sonic log was excellent. The tie in a deeper interval containing the reservoir was less satisfactory: the phase errors within the bandwidth of the seismic wavelet were of the order of 20°, which we consider too large for subsequent transformation of the data to seismic impedance. Reprocessing the seismic data and revision of the well-log model reduced these phase errors to less than 10° and improved the consistency of the deep and shallow well ties. The reprocessing included densely picked iterative velocity analysis, prestack migration, beam-forming multiple attenuation, stacking the near-offset traces and demigration and remigration of the near-offset data. The petrophysical model was used to monitor and, where necessary, replace the P-wave sonic log with predictions consistent with other logs and to correct the sonic log for mud-filtrate invasion in the hydrocarbon-bearing sand. This editing and correction of the P-wave transit times improved the normal-incidence well tie significantly. The recordings from a monopole source severely underestimated the S-wave transit times in soft shale formations, including the reservoir seal, where the S-wave velocity was lower than the P-wave velocity in the drilling mud. The petrophysical model predicted an S-wave log that matched the valid recordings and interpolated between them. The subsequent seismic modelling from the predicted S-wave log produced a class II AVO anomaly seen on the CDP gathers around the well.     

Azimuthal anisotropy analysis of walkaround vertical seismic profiling vertical seismic profiling: a case study from Saudi Arabia

Understanding fracture orientations is important for optimal field development of fractured reservoirs because fractures can act as conduits for fluid flow. This is especially true for unconventional reservoirs (e.g., tight gas sands and shale gas). Using walkaround Vertical Seismic Profiling (VSP) technology presents a unique opportunity to identify seismic azimuthal anisotropy for use in mapping potential fracture zones and their orientation around a borehole. Saudi Aramco recently completed the acquisition, processing and analysis of a walkaround VSP survey through an unconventional tight gas sand reservoir to help characterize fractures. In this paper, we present the results of the seismic azimuthal anisotropy analysis using seismic traveltime, shear‐wave splitting and amplitude attenuation. The azimuthal anisotropy results are compared to the fracture orientations derived from dipole sonic and image logs. The image log interpretation suggests that an orthorhombic fracture system is present. VSP data show that the P‐wave traveltime anisotropy direction is NE to SW. This is consistent with the cemented fractures from the image log interpretation. The seismic amplitude attenuation anisotropy direction is NW to SE. This is consistent with one of the two orientations obtained using transverse to radial amplitude ratio analysis, with the dipole sonic and with open fracture directions interpreted from image log data.     

A new laboratory technique for determining the compressional wave properties of marine sediments at sonic frequencies and in situ pressures

We describe a new laboratory technique for measuring the compressional wave velocity and attenuation of jacketed samples of unconsolidated marine sediments within the acoustic (sonic) frequency range 1–10 kHz and at elevated differential (confining – pore) pressures up to 2.413 MPa (350 psi). The method is particularly well suited to attenuation studies because the large sample length (up to 0.6 m long, diameter 0.069 m) is equivalent to about one wavelength, thus giving representative bulk values for heterogeneous samples. Placing a sediment sample in a water‐filled, thick‐walled, stainless steel Pulse Tube causes the spectrum of a broadband acoustic pulse to be modified into a decaying series of maxima and minima, from which the Stoneley and compressional wave, velocity and attenuation of the sample can be determined. Experiments show that PVC and copper jackets have a negligible effect on the measured values of sediment velocity and attenuation, which are accurate to better than ± 1.5% for velocity and up to ± 5% for attenuation. Pulse Tube velocity and attenuation values for sand and silty‐clay samples agree well with published data for similar sediments, adjusted for pressure, temperature, salinity and frequency using standard equations. Attenuation in sand decreases with pressure to small values below Q^?1 = 0.01 (Q greater than 100) for differential pressures over 1.5 MPa, equivalent to sub‐seafloor depths of about 150 m. By contrast, attenuation in silty clay shows little pressure dependence and intermediate Q^?1 values between 0.0206–0.0235 (Q = 49–43). The attenuation results fill a notable gap in the grain size range of published data sets. Overall, we show that the Pulse Tube method gives reliable acoustic velocity and attenuation results for typical marine sediments.     

Backus averaging,scattering and drift1

Differences between traveltimes from sonic to seismic frequencies, commonly known as drift, can be attributed to a combination of multiple scattering and absorption. The portion due to scattering can be estimated directly by calculating synthetic seismograms from sonic logs. A simple alternative approach is suggested by the long-wave equivalent averaging formulae for the effective elastic properties of a stack of thin layers, which gives the same traveltime delays as the low-frequency limit of the scattering dispersion. We consider the application of these averaging formulae over a frequency-dependent window with the hope of extending their use to frequencies higher than those allowed by the original validity conditions. However, comparison of the time delay due to window-averaging with the scattering dispersion predicted by the O'Doherty-Anstey formula reveals that it is not possible to specify a form of window that will fit the dispersion across the spectrum for arbitrary log statistics. A window with a width proportional to the wavelength squared matches the behaviour at the low-frequency end of the dispersive range for most logs, and allows an almost exact match of the drift across the entire spectrum for exponential correlation functions. We examine a real log, taken from a hole in nearly plane-layered geology, which displays strong quasi-cyclical variations on one scale as well as more random, smaller-scale fluctuations. The details of its drift behaviour are studied using simple models of the gross features. The form of window which gave a good theoretical fit to the dispersion for an exponential log correlation function can only fit the computed drift at high or low frequencies, confirming that there are at least two significant scale-lengths of fluctuation. A better overall fit is obtained for a window whose width is proportional to the wavelength. The calculated scattering drift is significantly less than that observed from a vertical seismic profile, but the difference cannot be wholly ascribed to absorption. This is because the source frequency of the sonic tool is not appropriate for its resolution (receiver spacing) so that the scattering drift from sonic to seismic frequencies cannot be fully estimated from the layer model derived from the log.     

泥质砂岩中接触胶结泥质定量估算及对砂岩弹性的影响

在泥质砂岩的岩石物理建模中,明确泥质砂岩中泥质胶结物的接触类型及其含量对正确认识泥质的胶结作用对泥质砂岩声速的影响以及合理地建立岩石物理模型至关重要.现阶段,尚未有实验室定量估算胶结泥质的方法,导致应用胶结砂岩理论模型预测胶结砂岩地层的声速时往往由于胶结物含量被高估从而导致预测声速结果偏高.本文通过观察铸体薄片中泥质与颗粒之间的接触关系和相对分布提出了一种区分胶结泥质和分散泥质的方法:与两个或两个以上颗粒接触的连续分布的泥质为胶结泥质;与一个颗粒接触或者不与颗粒接触的泥质为分散泥质.基于这一准则,本文基于像素拾取法估算了人造泥质砂岩的胶结泥质含量,并将胶结泥质含量作为胶结砂岩模型的输入参数优化CCT模型.对比原始模型,本文方法声速误差下降了20%,预测准确度显著提高.本文方法适用于弱胶结地层的岩石物理建模,能够准确的预测声速以结合地震和测井资料识别有利储层,定量评价储层参数.     

Modeling and interpretation of Q logs in carbonate rock using a double porosity model and well logs

Attenuation data extracted from full waveform sonic logs is sensitive to vuggy and matrix porosities in a carbonate aquifer. This is consistent with the synthetic attenuation (1 / Q) as a function of depth at the borehole-sonic source-peak frequency of 10 kHz. We use velocity and densities versus porosity relationships based on core and well log data to determine the matrix, secondary, and effective bulk moduli. The attenuation model requires the bulk modulus of the primary and secondary porosities. We use a double porosity model that allows us to investigate attenuation at the mesoscopic scale. Thus, the secondary and primary porosities in the aquifer should respond with different changes in fluid pressure. The results show a high permeability region with a Q that varies from 25 to 50 and correlates with the stiffer part of the carbonate formation. This pore structure permits water to flow between the interconnected vugs and the matrix. In this region the double porosity model predicts a decrease in the attenuation at lower frequencies that is associated with fluid flowing from the more compliant high-pressure regions (interconnected vug space) to the relatively stiff, low-pressure regions (matrix). The chalky limestone with a low Q of 17 is formed by a muddy porous matrix with soft pores. This low permeability region correlates with the low matrix bulk modulus. A low Q of 18 characterizes the soft sandy carbonate rock above the vuggy carbonate.This paper demonstrates the use of attenuation logs for discriminating between lithology and provides information on the pore structure when integrated with cores and other well logs. In addition, the paper demonstrates the practical application of a new double porosity model to interpret the attenuation at sonic frequencies by achieving a good match between measured and modeled attenuation.