S-wave Velocity Research Articles

Feasibility of Identifying Shale Sweet Spots by Downhole Microseismic Imaging

Several studies suggest that shale sweet spots are likely associated with a low Poisson’s ratio in the shale layer. Compared with conventional geophysical techniques with active seismic data, it is straightforward and cost-effective to delineate the distribution of 3D Poisson’s ratios using microseismic data. In this study, an alternating method is proposed to determine microseismic event locations, 3D P-wave velocity, and Poisson’s ratio models with data recorded from downhole monitoring arrays. The method combines the improved 3D traveltime tomography, which inverts P and S arrivals for 3D P-wave velocity and Poisson’s ratio structures simultaneously, and a 3D grid search approach for event locations in an iterative fashion. The traveltime tomography directly inverts the Poisson’s ratio structure instead of calculating the Poisson’s ratios from P- and S-wave velocities (i.e., Vp and Vs) that are inverted by conventional traveltime tomography separately. The synthetic results and analysis suggest that the proposed method recovers the true Poisson’s ratio model reasonably. Additionally, we apply the method to a field dataset, which indicates that it may help delineate the reservoir structure and identify potential shale sweet spots.

Shear wave measurement in slow formations for eccentric monopole acoustic logging while drilling

Abstract The use of a logging-while-drilling (LWD) monopole tool to directly measure shear (S) wave velocity in slow formations has been proven feasible under certain conditions. However, S-wave signals received in the borehole are fairly weak, which limits the application range of this measurement method. To find ways to enhance shear waves, we first explore factors sensitive to the S-wave excitation. Simulation results indicate that four parameters including the receiver-source distance, the radial distance from receiver to borehole wall, the formation S-wave velocity and source frequency, primarily influence the S-wave excitation. Shear waves can be enhanced by judiciously optimizing these parameters during tool design. We also investigate borehole wavefields with an eccentric LWD tool in both commonly slow and ultra-slow formations. Results reveal that tool eccentricity can amplify shear waves and improve its measurement accuracy, provided that waveforms received in the direction of tool movement are used. We successfully extracted the S-wave velocity of an ultra-slow formation under conditions of large eccentricity, while similar actions originally failed with a centralized instrument.

Wave velocities and anisotropy of rocks: Implication for origin of low velocity zone of the Qinling Orogenic Belt, China

Structure and composition of Earth is of fundamental importance in exploring the dynamic evolution of the crust and mantle. The Qinling Orogenic Belt (QOB) is located between the North China plate and the South China Plate, and is one of the main orogenic belts in China. To explore the composition and origin of anisotropy and the low wave velocity zone of the QOB, ten rock samples (gneiss and schist) were collected from the five sites of the QOB and the P- and S-wave velocities of these samples were measured under 0.6 to 2.0 GPa and 100 to 550 °C. The wave velocities increase with increasing pressure and decreasing temperature. The VP and VS of the schist and gneiss match the velocity of the middle and lower crust of the QOB, indicating that schist and gneiss are important component of the QOB. All the schist and gneiss samples exhibit obvious seismic anisotropy with 1.64%–17.42% for VS and 2.93%–14.78% for VP under conditions of crust and upper mantle. The CPO/LPO and layering distribution of mica in rock samples are the main reasons for this anisotropy. The VS structures below the five sampled sites from seismic ambient noise tomography were built to explore the effect of schist and gneiss on the composition and structure of the QOB. The results indicate that orientation-arranged gneiss and schist driven by the tectonic stresses might be a new origin of the character of VP/VS, seismic anisotropy, and the low velocity zone in the QOB.

Effects of 2.5-D ultra-low and ultra-high velocity zones on flip-reverse-stacking (FRS) of the ScS wavefield

SUMMARY Within the last decade, thin ultra-low velocity zone (ULVZ) layering, sitting directly on top of the core–mantle boundary (CMB), has begun to be investigated using the flip-reverse-stack (FRS) method. In this method, pre- and post-cursor arrivals that are symmetrical in time about the ScS arrival, but with opposite polarities, are stacked. This same methodology has also been applied to high velocity layering, with indications that ultra-high velocity zones (UHVZs) may also exist. Thus far, studies using the FRS technique have relied on 1-D synthetic predictions to infer material properties of ULVZs. 1-D ULVZ models predominantly show a SdS precursor that reflects off the top of the ULVZ and an ScscS reverberation within the ULVZ that arrives as a post-cursor. 1-D UHVZ models are more complex and have a different number of arrivals depending on a variety of factors including UHVZ thickness, velocity contrast, and lateral extent. 1-D modelling approaches assume that lower mantle heterogeneity is constant and continuous everywhere across the lower mantle. However, lower mantle features display lateral heterogeneity and are either finite in extent or display local thickness variations. We examine the interaction of the ScS wavefield with ULVZs and UHVZs in 2.5-D geometries of finite extent. We show that multiple additional arrivals exist that are not present in 1-D predictions. In particular, multipath ScS arrivals as well as additional post-cursor arrivals are generated. Subsequent processing by the FRS method generates complicated FRS traces with multiple peaks. Furthermore, post-cursor arrivals can be generated even when the ScS ray path does not directly strike the heterogeneity from above. Analysing these predictions for 2.5-D models using 1-D modelling techniques demonstrates that a cautious approach must be adopted in utilization and interpretation of FRS traces to determine if the ScS wavefield is interacting with a ULVZ or UHVZ through a direct strike on the top of the feature. In particular, traveltime delays or advances of the ScS arrival should be documented and symmetrical opposite polarity arrivals should be demonstrated to exist around ScS. The latter can be quantified by calculation of a time domain multiplication trace. Because multiple post-cursor arrivals are generated by finite length heterogeneities, interpretation should be confined to single layer models rather than to interpret the additional peaks as internal layering. Furthermore, strong trade-offs exist between S-wave velocity perturbation and thickness making estimations of ULVZ or UHVZ elastic parameters highly uncertain. We test our analysis methods using data from an event occurring in the Fiji-Tonga region recorded in North America. The ScS bounce points for this event sample the CMB region to the southeast of Hawaii, in a region where ULVZs have been identified in several recent studies. We see additional evidence for a ULVZ in this region centred at 14°N and 153°W with a lateral scale of at least 250 km × 360 km. Assuming a constant S-wave velocity decrease of −10 or −20 per cent with respect to the PREM model implies a ULVZ thickness of up to 16 or 9 km, respectively.

Influence of ice properties on wave propagation characteristics in partially frozen soils and rocks: A temperature-dependent rock-physics model

A better understanding of the temperature effects on the propagation characteristics of elastic waves in frozen soils and rocks is imperative for accurately quantifying their freezing degrees. Although the existing rock-physics models based on the three-phase Biot (TPB) theory adeptly interpret observed velocity variation with temperature (VVT) curves, they often lack a comprehensive understanding of the mechanisms underlying attenuation variation with temperature (AVT) curves. In this study, we first extend the TPB theory to incorporate the temperature-dependent properties of ice, such as changes in volumetric fraction, morphology, and viscoelasticity, by integrating the relevant thermodynamic laws. Model parameters related to ice properties and interactions, such as rigidity, shear moduli, density, and friction, are redefined. Then, using a numerical rock-physics modeling approach, we examine influential factors and modes of the wave VVT and AVT responses. Our results indicate that the P- and S-wave velocities increase with source frequency, consolidation degree, and frame-supporting ice content, whereas they decrease with temperature and pore-floating ice content. The P- and S-wave attenuation factors increase with the frame-supporting ice content and decrease with the consolidation degree. Rising temperatures tend to amplify the peak magnitude of the P-wave attenuation factors and shift the central frequency of the S-wave attenuation factors. Finally, within a temperature-controlled laboratory environment, we conduct ultrasonic wave transmission testing on brine-saturated sediment and rock specimens. The results demonstrate that as the temperature increases from −15°C to −3°C, the P- and S-wave velocities decrease, whereas the P-wave attenuation factors decrease and the S-wave attenuation factors initially rise before declining. Our viscoelastic TPB theory outperforms the existing ones in interpreting the S-wave AVT observations. This temperature-dependent rock-physics model holds promise for interpreting the sonic logging data in the time-lapse monitoring of permafrost, glaciers, and Antarctica.

Pore pressure prediction based on rock physics theory and its application in seismic inversion

Formation overpressure seriously affects drilling and downhole operation. Accurate prediction on the formation pore pressure can not only reduce the probability of drilling accidents, but also quantitatively evaluate the original formation pressure of underground pore space, which provides an important reference for site selection of carbon sink projects using underground space resources such as CO2 geological storage. It is therefore necessary to set up a widely applicable method that is based on rock physics theory and conforms to the characteristics of rock mechanics and fluid mechanic. This method is suitable for both logging prediction and seismic inversion of pore pressure. The traditional method of predicting pore pressure based on P-wave velocity has multiple solutions, and the prediction based on S-wave velocity which is not sensitive to fluid has new significance. Based on the Hertz-Mindlin petrophysical model that considering pressure variation and the Gassmann fluid substitution equation that addresses the change in fluid saturation, this paper firstly derived rock physical formulas for predicting pore pressure in logging, and then derived the intrinsic power function relationship between the effective pressure (Pe) and S-wave velocity (Vs) as well as S-wave impedance (Is). Based on this, a set of geophysical methods integrating S-wave velocity prediction, pore pressure prediction in well and seismic inversion is finally established. The efficacy of this method has been well validated, with an average error of 2.35% in S-wave velocities prediction, 4.5% in single-well pore pressure prediction. The results of seismic inversion of pore pressure are consistent with the phenomenon of overpressure development in actual working area. This method can be further extended to other areas, providing invaluable reference for underground operation such as oil and gas exploration and CO2 geological storage.

An efficient method of predicting S-wave velocity using sparse Gaussian process regression for a tight sandstone reservoir

The shear wave (S-wave) velocity plays a crucial role in interpreting the lithology in seismic data, identifying fluids and predicting reservoirs. However, S-wave velocity is often unavailable due to the high cost of measurement and technical constraints. Conventional methods exhibit limitations that potentially impact the accuracy or efficiency on predicting S-wave velocity. Moreover, these methods always ignore the uncertainty quantification associated with the predicted results. This paper proposes a sparse Gaussian process regression (SGPR) method to predict the S-wave velocity in tight sandstone reservoirs. SGPR is a highly efficient regression technique that is based on the Gaussian process regression (GPR) method. In the SGPR method, inducing inputs are introduced to approximate the kernel matrix to decrease the computational complexity. A sparse set of inducing inputs and kernel hyperparameters are optimized through minimizing the Kullback-Leibler (KL) divergence between the exact posterior distribution and the approximate one. In this study, we select several types of logging data, which include porosity, water saturation, shale content, lithology and P-wave velocity, as the inputs for the SGPR method to predict S-wave velocity. To validate its effectiveness, we use the SGPR method to predict S-wave velocity in tight sandstone and compare the results with those from the GPR method, the bidirectional long short-term memory (BiLSTM) method and the Xu-White model. Additionally, we conduct cross-validation to demonstrate the robustness of the SGPR method. Our findings indicate that the SGPR method presents better performance and significant advantages about the accuracy and efficiency. Moreover, the SGPR method offers uncertainty quantification for the predicted S-wave velocity.

Latent magmatism beneath the Korean Peninsula caused by asthenosphere upwelling

Volatiles such as helium and carbon dioxide provide insights into geological processes spanning from the Earth’s deep interior to its surface. Integration with geophysical data providing enhanced vertical resolution with a wider horizontal range better elucidates the mantle dynamics and its interactions with the crust. Here we present geochemistry of volatiles dissolved in fluid samples from fault-related springs, thermal spa waters, and groundwaters across the Korean Peninsula. These were examined in conjunction with existing geophysical information. Remarkably, there is a strong spatial correlation between helium isotopes and S-wave velocity, suggesting the influence of mantle upwelling on both geochemical and geophysical parameters. Furthermore, the computed helium flux is comparable to that of volcanic regions, implying partial melting induced by mantle upwelling due to edge-driven convection beneath the Korean Peninsula. Therefore, these findings suggest that mantle-derived volatiles can be released diffusely over large areas through faults in the modern Earth’s intraplate environment.

S-wave log construction through semi-supervised regression clustering using machine learning: A case study of North Sea fields

Accurate prediction of S-wave velocity from well logs is essential for understanding subsurface geological formations and hydrocarbon reservoirs. Machine learning techniques, including clustering and regression, have emerged as effective methods for indirectly estimating S-wave logs and other rock properties. In this study, we employed clustering algorithms to identify similarities among well log datasets, encompassing depth, sonic, porosity, neutron, and apparent density, facilitating the discovery of correlations among various wells. These identified correlations served as a foundation for predicting S-wave values using a novel semi-supervised approach. Our approach combined clustering, specifically k-means clustering, with different types of regressors, including Least Squares Regression (LSR), Support Vector Regression (SVR), and Multi-Layer Perceptron (MLP). Our results demonstrate the superior performance of this integrated approach compared to traditional regression methods. We validated our methodology using various parametric and non-parametric regression techniques, showcasing its effectiveness not only on wells within the training region but also on wells outside the study area. We achieved a significant improvement in the R2 score metric, ranging from 2.22% to 6.51%, and a reduction in Mean Square Error (MSE) of at least 31% when compared to predictions made without clustering. This study underscores the potential of machine learning techniques for accurate prediction of S-wave velocity and other rock properties, thereby enhancing our comprehension of subsurface geology and hydrocarbon reservoirs.

Seismic anisotropy of granitic rocks from a fracture stimulation well at Utah FORGE using ultrasonic measurements

For effective fracture stimulation in Enhanced Geothermal Systems (EGS), characterization of subsurface rock elastic properties is essential. Because seismic anisotropy significantly influences hydraulic fracturing, locating and characterizing microseismic events, and forecasting stress trajectories, our research undertakes laboratory experiments to study seismic anisotropy parameters of core samples from the Utah FORGE EGS site. We evaluated two rock samples from well 58–32, at two depths of 2074.16 m (6,805 feet) and 2268.01 m (7,441 feet), respectively. We analyze the mineralogy and classify the shallower rock as syenogranite, and the deeper rock as orthogneiss and monzonite. We cut cylindrical plugs from these two core samples, imaged them by computed tomography (CT) X-ray imaging, and measured their seismic anisotropy using ultrasonic waves at 1 MHz and under varying confining pressures (5–50 MPa) in ambient temperature conditions. With the assumption of the transversely isotropic (TI) medium, we measured three P-wave velocities and two S-wave velocities along different propagation directions to compute the Thomsen anisotropy parameters. Our results showed that the measured seismic velocities of each rock sample increase with increasing effective pressures, a behavior likely caused by closure of microcracks identified in our CT images. We also find that the measured anisotropies are higher at lower effective pressures. The maximum measured anisotropies for P-waves and S-waves are ∼23% and ∼20%, respectively. Therefore, we expect in the field operation that anisotropy should increase with increasing pore pressure caused by injection, which could be valuable in future EGS reservoir management and monitoring.

Porosity estimation based on the shear modulus inversion of seismic shear wave

Reliable estimation of subsurface porosity is necessary for hydrocarbon reservoir characterization and fluid identification. Porosity estimations from seismic data can provide the lateral distribution of subsurface porosity, but the results may be highly nonunique because subsurface elastic properties (such as velocity and density) can be affected by porosity and pore fluids. Because shear modulus is insensitive to pore fluid content, it can be effectively used to estimate porosity. We develop a novel porosity estimation method using the reflected SH wave (SH-SH wave), whose propagation characteristics depend mainly on shear modulus and S-wave velocity. We derive a new analytical expression for the SH-SH-wave reflection coefficient, which acts as a function of shear modulus and S-wave velocity in its natural logarithm form. This new approximation has high accuracy, and both coefficients corresponding to shear modulus and S-wave velocity are “model-parameter independent”; thus, there is no need for prior estimation of any model parameter during inversion. Numerical analysis indicates that shear modulus inverted from the SH-SH wave has lower uncertainty, the problem is better conditioned, and the method requires data with fewer incidence angles than algorithms that invert for the shear modulus from the PP wave. Furthermore, the highly correlated rock-physics relationships between porosity and shear modulus facilitate accurate porosity estimation. A field data application indicates that high-resolution porosity of fine structures can be reliably recovered using our method.

An Experimental Investigation on the Effects of Temperature and Confining Pressure on the Static and Dynamic Behaviors of Shale Rocks

Abstract To better understand the associated thermal and mechanical effects on the elastic behaviors of shale rocks, we examine the shale rocks at reservoir stress (static) and elastic conditions (dynamic) at varying temperature (25–110°C) and pressure (5–55 MPa) conditions through coupling dynamic–static experimental measurements. The results illustrate that the shale’s P- and S-wave velocities increase with the increasing confining pressure but decrease with the elevated temperature. For the pressure history, ultrasonic P-wave velocities upon hydrostatic unloading are slightly larger than the loading ones, whereas S-wave velocities are almost overlapping together. Meanwhile, the temperature elevation causes much less velocity reduction at a higher confining pressure than lower confining pressure. The measured data demonstrate that the static bulk modulus is more sensitive to the confining pressure than the dynamic bulk modulus. Moreover, with the elevated temperature, the dynamic bulk moduli separate by showing a decreasing trend in either hydrostatic loading or unloading. The loading–unloading cycle shows that the static bulk moduli present values approaching the dynamic ones at all temperature levels when the confining pressure is initially unloaded from the maximum pressure. Both static and dynamic bulk moduli decrease with the continued unloading, with more decrement for the static bulk modulus. The coupling effects of the pressure and temperature on the static and elastic properties of shale samples imply that, in the practical shale reservoir characterization process, temperature and pressure influences should be considered to characterize the relation of dynamic and static properties of shale rocks. The laboratory investigations on shales imply that the relation of dynamic and static properties is pressure dependent mainly due to the intrinsic behavior of fracture, soft pore, and microstructure in the rock frame.

Study on mechanical properties and damage characteristics of acid corrosion in granite based on NMR technology

In acidic environments, rock masses are frequently subjected to severe chemical corrosion, resulting in the initiation of numerous geological engineering disasters. This study aimed to collect physical and mechanical parameters of granite exposed to prolonged acid corrosion and analyze fracture characteristics using acoustic emission (AE) techniques. Additionally, it examined the evolution of pore structure and damage mechanisms through the use of low-field nuclear magnetic resonance (NMR) and fractal theory. The results demonstrate a monotonic decrease in mass, volume, density, P-wave velocity, and S-wave velocity of granite with increasing corrosion time. Particularly notable is the phased reduction observed in uniaxial compressive strength and elastic modulus. The transition from brittle to ductile failure in corroded granite is accompanied by a gradual decrease in internal fracture strength. The trend in the correlation dimension reveals the relationship between the formation time of the main fracture surface and the pore structure. Additionally, total porosity and macropores (D, Da) exhibit significant fractal characteristics. The fractal dimension correlates positively with the damage variable and inversely with uniaxial compressive strength and elastic modulus. This indicates that more severe pore structure damage leads to a higher fractal dimension and lower mechanical performance. Among these, Da demonstrates higher sensitivity in characterizing rock mechanical properties. These findings provide important basis for evaluating the stability of granite geotechnical engineering in acidic environments.

Crustal thicknesses in Uruguay from joint inversion of receiver functions and surface wave dispersion

The development of a seismic network in Uruguay in recent years has enabled studies of crustal structure in a region with few seismological studies of this type. In this work, we update the crustal thicknesses and Vp/Vs ratios calculated by H-k stack and present S-wave velocity models based on joint inversion of receiver functions and Rayleigh wave group velocity dispersion curves.Some interesting results are the presence of a lower crust with a high S-wave velocity of 4.1 km/s below one of the stations located on the Río de la Plata Craton and the existence of a transitional Moho in Uruguay's northernmost station on the Paraná Basin, perhaps suggesting the presence of localized underplated material. A relatively thick crust, 41.8 km, compared to surrounding stations, was found beneath the Sierra Ballena Shear Zone in the Dom Feliciano Belt. We confirm the decrease in crustal thickness when approaching the oceanic coast, reaching a Moho depth of 36.3 km in SE Uruguay. Finally, the calculated Poisson's ratio allows inferring a crust of felsic to intermediate composition beneath most of Uruguay.

Left ventricular dysfunction in pulmonary arterial hypertension is attributed to underfilling rather than intrinsic myocardial disease: a CMR 2D phase contrast study

The pathophysiology underlying impaired LV function in PAH remains unclear, with some studies implicating intrinsic myocardial dysfunction and others pointing to LV underfilling. Evaluation of pulmonary vein area (PVA) and flow may offer novel, mechanistic insight by distinguishing elevated LV filling pressure common in myocardial dysfunction from LV underfilling. This study aimed to elucidate LV filling physiology in PAH by assessing PVA and flow using cardiac magnetic resonance (CMR) and compare pulmonary vein flow in PAH with HFrEF as a model representing elevated filling pressures, in addition to healthy controls. Patients with PAH or heart failure with reduced ejection fraction (HFrEF) referred for CMR were retrospectively reviewed, and healthy controls were included as reference. Pulmonary vein S, D and A-wave were compared between groups. Associations between pulmonary vein area (PVA) by CMR and echocardiographic indices of LV filling pressure were evaluated. Nineteen patients with PAH, 25 with HFrEF and 24 controls were included. Both PAH and HFrEF had lower ejection fraction and S-wave velocity than controls. PAH displayed smaller LV end-diastolic volumes than controls, while HFrEF demonstrated larger PVA and higher A-wave reversal. PVA was associated with mitral E/e′ ratio (r2 = 0.10; p = 0.03), e′ velocity (r2 = 0.23; p = 0.001) and left atrial volume (r2 = 0.07; p = 0.005). Among PAH, PVA was not associated with LV-GLS. A PVA cut-off of 2.3cm2 displayed 87% sensitivity and 72% specificity to differentiate HFrEF and PAH (AUC = 0.82). PAH displayed lower pulmonary vein S-wave velocity, smaller LV volume and reduced function compared with controls. Reduced LV function in PAH may be owing to underfilling rather than intrinsic myocardial disease. PVA demonstrates promise as a novel, non-invasive imaging marker to assess LV filling status.

Correlated crustal and mantle melting documents proto-Tibetan Plateau growth.

The mechanism that causes the rapid uplift and active magmatism of the Hoh-Xil Basin in the northern Tibetan Plateau and hence the outward growth of the proto-plateau is highly debated, more specifically, over the relationship between deep dynamics and surface uplift. Until recently the Hoh-Xil Basin remained uncovered by seismic networks due to inaccessibility. Here, based on linear seismic arrays across the Hoh-Xil Basin, we present a three-dimensional S-wave velocity (VS) model of the crust and uppermost mantle structure beneath the Tibetan Plateau from ambient noise tomography. This model exhibits a widespread partially molten crust in the northern Tibetan Plateau but only isolated pockets in the south manifested as low-VS anomalies in the middle crust. The spatial correlation of the widespread low-VS anomalies with strong uppermost mantle low-VS anomalies and young exposed magmatic rocks in the Hoh-Xil Basin suggests that the plateau grew through lithospheric mantle removal and its driven magmatism.

Prediction of tight sandstone reservoirs by multiwave joint prestack inversion technology: A case study of the Qiulin area in the Sichuan Basin

The Shaximiao (SXM) Formation of the Middle Triassic in the central Sichuan Basin is a river-lake sedimentary system with an average burial depth of 2800 m. The channel sand bodies of the SXM Formation in the Qiulin area are developed with large lateral variation and high- and medium-porosity sand. This leads to great differences in the seismic response and difficulty in predicting the sand bodies and reservoirs using P-wave data. We carry out well-log analysis for different types of sand bodies. The no. 8 sand body of high porosity can be effectively identified using P-wave impedance (PI). Whereas for the no. 7 sand body of relatively lower porosity (mainly due to the higher shale content in the no. 7 sand compared with the no. 8 sand), sandstone and mudstone can be distinguished using S-wave impedance (SI), and reservoirs can be recognized by the P- to S-wave velocity ratio ([Formula: see text]/[Formula: see text]). Based on the PP wave and the P-to-S converted wave (PS wave) (after matching) angle-stacked data, a prestack inversion of multicomponent data is performed. Multiwave joint inversion results (SI and [Formula: see text]/[Formula: see text]) have better accuracy and stronger stability than the PP-wave inversion in practical application. In addition, the PI of the joint inversion more clearly describes the distribution and boundaries of the channel sand and better matches the prediction and drilling data in sand 8. The SI of the joint inversion can identify subtle sand bodies (weak PI contrast) that are difficult to be detected by PP-wave inversion. The distribution of the reservoir predicted by the [Formula: see text]/[Formula: see text] of the joint inversion is clearer (the no. 7 sand body) and better than that by the PP-wave inversion. This study demonstrates the advantage of the multiwave joint inversion technology in tight sand identification.

Lithospheric structure of the Paraná, Chaco-Paraná, and Pantanal basins: Insights from ambient noise and earthquake-based surface wave tomography

To investigate the lithospheric seismic structure of southern South America beneath the Paraná, Chaco-Paraná, and Pantanal basins, we measure two distinct sets of dispersion curves of Rayleigh waves: the first corresponds to 25,986 phase velocity dispersion curves in the period range 5–50 s, extracted from cross-correlation of the ambient noise between pairs of stations and thus sensitive mainly to crustal structure; the second set is derived from group velocities extracted from earthquake recordings, resulting in 33,888 dispersion curves with periods ranging from 8 to 200 s, allowing us to probe deeper Earth structure. From these data sets, we derive two independent S-wave velocity models following a two-step inversion procedure, resulting in a crustal and a lithospheric mantle model with depths extending up to 50 and 200 km, respectively. Features imaged in our crustal model include low velocity anomalies in agreement with the surface position of the major sedimentary basins and high velocity anomalies within fold-thrust provinces and the basement of the Pantanal basin. In the uppermost mantle, we identify high velocities in the region of the Paraná basin, São Francisco and Amazonian cratons, and Luiz Alves block, and a low velocity feature beneath the Pantanal basin, which suggests a potentially thinner lithosphere under the basin. We also illuminate a strong velocity gradient boundary between the eastern border of the Pantanal basin with the Paraná basin, from crustal to lithospheric mantle depths, which seems to delineate the western and southern borders of the Paraná basin, coinciding with the Western Paraná Suture. Additionally, we construct a Moho depth proxy map for the study area, which has an overall good agreement with previous results, except for a thicker crust beneath the southern Chaco-Paraná basin. This area, together with a thicker crust counterpart in the Paraná basin, has a remarkable correlation with the position of a volcanic layer related to the Paraná Magmatic Province, which leads us to suggest that magmatic processes played an important role in the south Chaco-Paraná basin as well.

Exploring geothermal resources with the CSAMT and microtremor methods: a case study in Tangquan, Jiangsu Province, China

The development of geothermal energy has received extensive attention because of global energy scarcity and environmental pollution. The Tangquan area is in the north of the Yangtze fold belt, and the lack of magmatic rock development has resulted in a low-temperature type of geothermal reservoir. There are sporadic hot springs and cold springs exposed in the study area, but the uncertain deep geological structure, unknown geothermal reservoir formation mechanism, and lack of detailed exploration data seriously restrict the exploration and development of geothermal resources in the area. Filling underground faults with water can significantly reduce electrical resistivity, while traps filled with warm water can cause a decrease in S-wave velocity. Thus, a new integrated geophysical method, including the controlled source audio-frequency magnetotelluric (CSAMT) and microtremor methods, is applied for geothermal exploration in the region. The combination of CSAMT and microtremor methods can determine thermal-controlled and water-conducting structures more effectively and locate geothermal storage more accurately. The source, channel, storage, and cover of regional geothermal reservoir formation are analyzed using geophysical and geological data. That is, the regional NE- and NW-trending faults are explained as thermal-controlled and water-conducted structures, respectively. The deep Sinian Dengying Formation supplies a heat- and water-bearing space. The tectonic intersection area, especially the tensional fault zone, is found to be closely related to the existence of geothermal reservoirs, which is well verified by later drilling results. Finally, a geothermal reservoir model is established to comprehensively understand the distribution of geothermal energy in the region.

Bayesian linearized inversion for petrophysical and pore-connectivity parameters with seismic elastic data of carbonate reservoirs

Abstract Carbonate reservoirs are important targets for promoting the oil and gas reserve exploration and production in China. However, such reservoirs usually contain the developed complex pore structures, which heavily affect the precision in seismic prediction of petrophysical parameters. As one of the most important parameters to characterize reservoir rock, pore-related parameters can not only describe the pore structure, but also be used to evaluate the oil/gas bearing capabilities of potential reservoirs. The conventional rock-physics models (e.g. Gassmann's model) are formulated assuming fully-connected pores, which is unable to accurately capture the geometrical complexity in real rocks. In order to characterize the influences of multiple pores on the elastic properties, this work presents a rock-physics modelling method for carbonates, wherein the percentage composition of connected pores is equivalently quantified as the pore-connectivity factor. The method treats the pore-connectivity factor as an objective variable to characterize the spatial variations of pore structure. Specifically, the method combines the differential equivalent medium theory and Gassmann's model, and derives a linearized forward operator to quantitatively link porosity, water saturation, and pore-connectivity factor to seismic elastic parameters. According to the Bayesian linear inverse theory, the simultaneous estimation of petrophysical and pore-connectivity parameters is achieved. To characterize the statistical variations with multiple lithofacies, the Gaussian mixture model is employed to quantify the prior distribution of the objective variables. The posterior distribution of the objective variables is analytically expressed with the linearized forward operator. Numerical experiments show that the accuracy of the proposed method in predicting elastic parameters is improved. Compared with the conventional Xu-White model and the varying pore aspect ratio method, the accuracy of predicted P-wave velocity increases by 10.29% and 1.33%, respectively, and the predicted S-wave velocity increases by 6.44% and 0.03%, in terms of correlation coefficient. The application to the field data validates the effectiveness of the method, wherein the porosity and water saturation results help indicating the spatial distribution of potential reservoirs.