Relating Acoustic Anisotropy to Kerogen Content in Unconventional Formations - A Case Study in A Kerogen-Rich Unconventional Carbonate

2021 ◽  
Author(s):  
Yair Gordin ◽  
Thomas Bradley ◽  
Yoav O. Rosenberg ◽  
Anat Canning ◽  
Yossef H. Hatzor ◽  
...  
Keyword(s):  
Wave Velocity ◽  
Water Saturation ◽  
Well Logs ◽  
Rock Properties ◽  
Thermal Maturity ◽  
Burial Diagenesis ◽  
S Wave ◽  
Velocity Anisotropy ◽  
Thermal Maturation ◽  
Wide Range

Abstract The mechanical and petrophysical behavior of organic-rich carbonates (ORC) is affected significantly by burial diagenesis and the thermal maturation of their organic matter. Therefore, establishing Rock Physics (RP) relations and appropriate models can be valuable in delineating the spatial distribution of key rock properties such as the total organic carbon (TOC), porosity, water saturation, and thermal maturity in the petroleum system. These key rock properties are of most importance to evaluate during hydrocarbon exploration and production operations when establishing a detailed subsurface model is critical. High-resolution reservoir models are typically based on the inversion of seismic data to calculate the seismic layer properties such as P- and S-wave impedances (or velocities), density, Poisson's ratio, Vp/Vs ratio, etc. If velocity anisotropy data are also available, then another layer of data can be used as input for the subsurface model leading to a better understanding of the geological section. The challenge is to establish reliable geostatistical relations between these seismic layer measurements and petrophysical/geomechanical properties using well logs and laboratory measurements. In this study, we developed RP models to predict the organic richness (TOC of 1-15 wt%), porosity (7-35 %), water saturation, and thermal maturity (Tmax of 420-435⁰C) of the organic-rich carbonate sections using well logs and laboratory core measurements derived from the Ness 5 well drilled in the Golan Basin (950-1350 m). The RP models are based primarily on the modified lower Hashin-Shtrikman bounds (MLHS) and Gassmann's fluid substitution equations. These organic-rich carbonate sections are unique in their relatively low burial diagenetic stage characterized by a wide range of porosity which decreases with depth, and thermal maturation which increases with depth (from immature up to the oil window). As confirmation of the method, the levels of organic content and maturity were confirmed using Rock-Eval pyrolysis data. Following the RP analysis, horizontal (HTI) and vertical (VTI) S-wave velocity anisotropy were analyzed using cross-dipole shear well logs (based on Stoneley waves response). It was found that anisotropy, in addition to the RP analysis, can assist in delineating the organic-rich sections, microfractures, and changes in gas saturation due to thermal maturation. Specifically, increasing thermal maturation enhances VTI and azimuthal HTI S-wave velocity anisotropies, in the ductile and brittle sections, respectively. The observed relationships are quite robust based on the high-quality laboratory and log data. However, our conclusions may be limited to the early stages of maturation and burial diagenesis, as at higher maturation and diagenesis the changes in physical properties can vary significantly.

scholarly journals Research on prediction method of S-wave velocity based on deep learning

2021 ◽  
Vol 2083 (4) ◽  
pp. 042065
Author(s):  
Guojie Yang ◽  
Shuhua Wang
Keyword(s):  
Deep Learning ◽  
Wave Velocity ◽  
Prediction Method ◽  
P Wave ◽  
Learning Technology ◽  
S Wave ◽  
Advantages And Disadvantages ◽  
Wave Prediction ◽  
Wide Range ◽  
Velocity Prediction

Abstract Aiming at the s-wave velocity prediction problem, based on the analysis of the advantages and disadvantages of the empirical formula method and the rock physics modeling method, combined with the s-wave velocity prediction principle, the deep learning method is introduced, and a deep learning-based logging s-wave velocity prediction method is proposed. This method uses a deep neural network algorithm to establish a nonlinear mapping relationship between reservoir parameters (acoustic time difference, density, neutron porosity, shale content, porosity) and s-wave velocity, and then applies it to the s-wave velocity prediction at the well point. Starting from the relationship between p-wave and s-wave velocity, the study explained the feasibility of applying deep learning technology to s-wave prediction and the principle of sample selection, and finally established a reliable s-wave prediction model. The model was applied to s-wave velocity prediction in different research areas, and the results show that the s-wave velocity prediction technology based on deep learning can effectively improve the accuracy and efficiency of s-wave velocity prediction, and has the characteristics of a wide range of applications. It can provide reliable s-wave data for pre-stack AVO analysis and pre-stack inversion, so it has high practical application value and certain promotion significance.

Useful approximations for converted‐wave AVO

Geophysics ◽  
2001 ◽  
Vol 66 (6) ◽  
pp. 1721-1734 ◽  
Author(s):  
Antonio C. B. Ramos ◽  
John P. Castagna
Keyword(s):  
Wave Velocity ◽  
Random Noise ◽  
P Wave ◽  
Rock Properties ◽  
Negative Slope ◽  
High Contrast ◽  
Fractional Change ◽  
S Wave ◽  
Converted Wave ◽  
Low Contrast

Converted‐wave amplitude versus offset (AVO) behavior may be fit with a cubic relationship between reflection coefficient and ray parameter. Attributes extracted using this form can be directly related to elastic parameters with low‐contrast or high‐contrast approximations to the Zoeppritz equations. The high‐contrast approximation has the advantage of greater accuracy; the low‐contrast approximation is analytically simpler. The two coefficients of the low‐contrast approximation are a function of the average ratio of compressional‐to‐shear‐wave velocity (α/β) and the fractional changes in S‐wave velocity and density (Δβ/β and Δρ/ρ). Because of its simplicity, the low‐contrast approximation is subject to errors, particularly for large positive contrasts in P‐wave velocity associated with negative contrasts in S‐wave velocity. However, for incidence angles up to 40° and models confined to |Δβ/β| < 0.25, the errors in both coefficients are relatively small. Converted‐wave AVO crossplotting of the coefficients of the low‐contrast approximation is a useful interpretation technique. The background trend in this case has a negative slope and an intercept proportional to the α/β ratio and the fractional change in S‐wave velocity. For constant α/β ratio, an attribute trace formed by the weighted sum of the coefficients of the low‐contrast approximation provides useful estimates of the fractional change in S‐wave velocity and density. Using synthetic examples, we investigate the sensitivity of these parameters to random noise. Integrated P‐wave and converted‐wave analysis may improve estimation of rock properties by combining extracted attributes to yield fractional contrasts in P‐wave and S‐wave velocities and density. Together, these parameters may provide improved direct hydrocarbon indication and can potentially be used to identify anomalies caused by low gas saturations.

scholarly journals On the Effect of CO2 on Seismic and Ultrasonic Properties: A Novel Shale Experiment

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 5007
Author(s):  
Stian Rørheim ◽  
Mohammad Hossain Bhuiyan ◽  
Andreas Bauer ◽  
Pierre Rolf Cerasi
Keyword(s):  
Young’S Modulus ◽  
Wave Velocity ◽  
Poisson’S Ratio ◽  
Young's Modulus ◽  
Co2 Storage ◽  
Poisson's Ratio ◽  
Rock Properties ◽  
S Wave ◽  
Velocity Changes ◽  
4D Seismic

Carbon capture and storage (CCS) by geological sequestration comprises a permeable formation (reservoir) for CO2 storage topped by an impermeable formation (caprock). Time-lapse (4D) seismic is used to map CO2 movement in the subsurface: CO2 migration into the caprock might change its properties and thus impact its integrity. Simultaneous forced-oscillation and pulse-transmission measurements are combined to quantify Young’s modulus and Poisson’s ratio as well as P- and S-wave velocity changes in the absence and in the presence of CO2 at constant seismic and ultrasonic frequencies. This combination is the laboratory proxy to 4D seismic because rock properties are monitored over time. It also improves the understanding of frequency-dependent (dispersive) properties needed for comparing in-situ and laboratory measurements. To verify our method, Draupne Shale is monitored during three consecutive fluid exposure phases. This shale appears to be resilient to CO2 exposure as its integrity is neither compromised by notable Young’s modulus and Poisson’s ratio nor P- and S-wave velocity changes. No significant changes in Young’s modulus and Poisson’s ratio seismic dispersion are observed. This absence of notable changes in rock properties is attributed to Draupne being a calcite-poor shale resilient to acidic CO2-bearing brine that may be a suitable candidate for CCS.

Converted-wave model building and imaging based on common-focus-point methodology

Geophysics ◽  
2020 ◽  
Vol 85 (6) ◽  
pp. U139-U149
Author(s):  
Hongwei Liu ◽  
Mustafa Naser Al-Ali ◽  
Yi Luo
Keyword(s):  
Elastic Wave ◽  
Wave Velocity ◽  
Seismic Data ◽  
Model Building ◽  
P Wave ◽  
Rock Properties ◽  
S Wave ◽  
Converted Wave ◽  
Seismic Images ◽  
Focus Point

Seismic images can be viewed as photographs for underground rocks. These images can be generated from different reflections of elastic waves with different rock properties. Although the dominant seismic data processing is still based on the acoustic wave assumption, elastic wave processing and imaging have become increasingly popular in recent years. A major challenge in elastic wave processing is shear-wave (S-wave) velocity model building. For this reason, we have developed a sequence of procedures for estimating seismic S-wave velocities and the subsequent generation of seismic images using converted waves. We have two main essential new supporting techniques. The first technique is the decoupling of the S-wave information by generating common-focus-point gathers via application of the compressional-wave (P-wave) velocity on the converted seismic data. The second technique is to assume one common VP/ VS ratio to approximate two types of ratios, namely, the ratio of the average earth layer velocity and the ratio of the stacking velocity. The benefit is that we reduce two unknown ratios into one, so it can be easily scanned and picked in practice. The PS-wave images produced by this technology could be aligned with the PP-wave images such that both can be produced in the same coordinate system. The registration between the PP and PS images provides cross-validation of the migrated structures and a better estimation of underground rock and fluid properties. The S-wave velocity, computed from the picked optimal ratio, can be used not only for generating the PS-wave images, but also to ensure well registration between the converted-wave and P-wave images.

EXPERIMENTAL EVALUATION OF ULTRASONIC VELOCITIES AND ANISOTROPY IN THE TUSCALOOSA MARINE SHALE FORMATION

2020 ◽  
pp. 1-62 ◽  
Author(s):  
Jamal Ahmadov ◽  
Mehdi Mokhtari
Keyword(s):  
Wave Velocity ◽  
Mineralogical Composition ◽  
Organic Content ◽  
P Wave ◽  
S Wave ◽  
Velocity Anisotropy ◽  
Wave Velocities ◽  
Marine Shale ◽  
P Wave Velocity ◽  
Degree Of Anisotropy

Tuscaloosa Marine Shale (TMS) formation is a clay- and organic-rich emerging shale play with a considerable amount of hydrocarbon resources. Despite the substantial potential, there have been only a few wells drilled and produced in the formation over the recent years. The analyzed TMS samples contain an average of 50 wt% total clay, 27 wt% quartz and 14 wt% calcite and the mineralogy varies considerably over the small intervals. The high amount of clay leads to pronounced anisotropy and the frequent changes in mineralogy result in the heterogeneity of the formation. We studied the compressional (VP) and shear-wave (VS) velocities to evaluate the degree of anisotropy and heterogeneity, which impact hydraulic fracture growth, borehole instabilities, and subsurface imaging. The ultrasonic measurements of P- and S-wave velocities from five TMS wells are the best fit to the linear relationship with R2 = 0.84 in the least-squares criteria. We observed that TMS S-wave velocities are relatively lower when compared to the established velocity relationships. Most of the velocity data in bedding-normal direction lie outside constant VP/VS lines of 1.6–1.8, a region typical of most organic-rich shale plays. For all of the studied TMS samples, the S-wave velocity anisotropy exhibits higher values than P-wave velocity anisotropy. In the samples in which the composition is dominated by either calcite or quartz minerals, mineralogy controls the velocities and VP/VS ratios to a great extent. Additionally, the organic content and maturity account for the velocity behavior in the samples in which the mineralogical composition fails to do so. The results provide further insights into TMS Formation evaluation and contribute to a better understanding of the heterogeneity and anisotropy of the play.

scholarly journals VP/VS ratio and shear-wave splitting in the Nankai Trough seismogenic zone: Insights into effective stress, pore pressure, and sediment consolidation

Geophysics ◽  
2011 ◽  
Vol 76 (3) ◽  
pp. WA71-WA82 ◽  
Author(s):  
Takeshi Tsuji ◽  
Jack Dvorkin ◽  
Gary Mavko ◽  
Norimitsu Nakata ◽  
Toshifumi Matsuoka ◽  
...  
Keyword(s):  
Pore Pressure ◽  
Wave Velocity ◽  
Seismogenic Zone ◽  
Polarization Direction ◽  
S Wave ◽  
Velocity Anisotropy ◽  
Wave Splitting ◽  
Sediment Consolidation ◽  
Converted Waves ◽  
Plate Subduction

To estimate variation of stress state and sediment consolidation in the Nankai plate subduction zone off southwest Japan, we measured the P-wave to S-wave velocity ratio (VP/VS) and S-wave splitting along the seismic line extending from the trench to the seismogenic zone. For this purpose, we used active-source seismic data recorded by multicomponent ocean bottom seismometers (OBS). Because it is difficult to identify the PS-converted reflection waveforms for each of the geological boundaries in this deep offshore region, we focused on the more easily identified PPS-refracted waveforms that register the conversion of the up-going P-waves to S-waves at the igneous crust surface. We estimated the average VP/VS ratio within the sedimentary section by using the time lag between the P-refracted waves and PPS-converted waves. This VP/VS ratio changes abruptly at the trough axis (i.e., the deformation front of the accretionary prism) arguably because of compaction associated with the accretion process. We observed relatively high VP/VS around the seismogenic megasplay fault, which may partially indicate the abnormal pore pressure and intensive fractures associated with the fault. To estimate the stress-induced fracture orientation and stress magnitude, we computed the fast S-wave polarization direction and estimated S-wave velocity anisotropy by applying the crosscorrelation method to the PPS-converted waves. To improve signal-to-noise ratio of the waveform for S-wave splitting analysis, we stacked PPS-converted waveforms on receiver gather. These anisotropic characteristics change at the seismogenic megasplay fault: the fast polarization direction is nearly parallel to the subduction direction seaward of the megasplay fault and is perpendicular to the subduction direction landward of the megasplay fault. This velocity anisotropy is especially strong around the megasplay fault. These results imply that the preferred fracture orientation, as well as the principal stress orientation, is oblique to the direction of plate subduction near the megasplay fault.

Rock properties of smectite- and ooze-rich claystones

Geophysics ◽  
2015 ◽  
Vol 80 (1) ◽  
pp. D89-D98 ◽  
Author(s):  
Bente Øygarden ◽  
Helge Løseth ◽  
Sigurd Njerve
Keyword(s):  
Wave Velocity ◽  
Rock Properties ◽  
Environmental Scanning ◽  
S Wave ◽  
Amplitude Variation With Offset ◽  
Lower Miocene ◽  
Lower Oligocene ◽  
Upper Oligocene ◽  
Northern North Sea ◽  
New Equation

Parameters measured by well logs define rock properties and seismic reflections at lithology interfaces. Parameters from standard embedding claystones are normally used when calculating the top sand amplitude variation with offset (AVO) response, but this might give erroneous results when the real claystone rock properties deviate from the standard. Using cuttings and high-quality wireline logs from well 34/8-A-33 H above the Visund field in the northern North Sea, we evaluated rock properties of the Pleistocene glaciomarine claystones, Lower Miocene and Upper Oligocene oozy claystones, Lower Oligocene and Eocene smectite-rich claystones, and two interbedded sands. Glaciomarine claystones fit best with the Greenberg-Castagna equation and have the highest measured velocities even though they are the shallowest buried sediments. Environmental scanning electron microscope analysis proves the Lower Miocene and Upper Oligocene claystones to be oozy. The amount of low-density oozy material causes significant shifts in the log curves and makes the ooze-rich claystones plot far off the trend given by the Greenberg-Castagna equation. We, therefore, developed a new equation for S-wave velocity prediction for ooze-rich claystones with average densities between [Formula: see text] and [Formula: see text]. The [Formula: see text] ratios increase with depth in the Lower Oligocene and Eocene claystones of the Hordaland Group, and we interpreted this to reflect a downward increase in the amount of smectite, which existence was proven by X-ray diffraction analysis. We modeled how the seismic response at the top of a sand changes with embedding claystone type, saturation fluid, and offset. In glaciomarine claystones, the top of a brine-saturated sand corresponds to a negative trough reflection, in ooze-rich claystones to a positive peak reflection, and in smectite-rich claystones the reflection amplitude is close to zero. The predicted AVO response of sands in oozy claystones is highly dependent on whether the measured or calculated S-wave velocity has been used in the modeling.

Premonitory Variations in S-Wave Velocity Anisotropy before Earthquakes in Nevada

Science ◽  
1973 ◽  
Vol 182 (4117) ◽  
pp. 1129-1132 ◽  
Author(s):  
I. N. Gupta
Keyword(s):  
Wave Velocity ◽  
S Wave ◽  
Velocity Anisotropy

scholarly journals An Experimental Study of Velocity-Saturation Relationships in Volcanic Rocks

2015 ◽  
Vol 8 (1) ◽  
pp. 142-152 ◽  
Author(s):  
Zhidi Liu ◽  
Jingzhou Zhao
Keyword(s):  
Wave Velocity ◽  
Water Saturation ◽  
Velocity Ratio ◽  
Volcanic Rocks ◽  
Junggar Basin ◽  
S Wave ◽  
Gas Reservoirs ◽  
Velocity Saturation ◽  
Wave Velocities ◽  
Water Saturated

In this paper, experiments are carried out under different pressures and water saturations using core samples of volcanic rocks from the Junggar Basin in China to understand how water saturation affects P- and S-wave velocities. The results show that water saturated rocks exhibit significantly higher P- and S-wave velocities than gas saturated rocks. In addition, the P- and S-wave velocity ratio declines with increasing water saturation. Furthermore, a P- and S-wave velocity ratio vs. resistivity cross plot is created to identify gas reservoirs in the volcanic rocks in the Junggar Basin.

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