Investigating the influence of mineralogy and pore shape on the velocity of carbonate rocks: Insights from extant global data sets

Using a variety of recent public-domain data sets comprising porosity, velocity (P- and S-waves), and, in most cases, mineralogy and petrographic data, I created an extensive global data set and evaluated the importance of mineralogy and pore type on the elastic properties behavior of carbonate core plugs. Results from this investigation clearly illuminated the potential for overinterpreting elastic properties behavior as a function of pore type(s) when mineralogy was not explicitly included in the analysis. Rock-physics analysis using a combination of heuristic and theoretical models illustrated that mineralogy exerted a significant additional variation on velocity at a given porosity. Failure to account for mineralogy exacerbated inferences about the effect of pore type(s) made using a comparison of P-wave velocity to an inappropriate empirical model (Wyllie) that did not account for pore shape(s). In this analysis, extreme variability in carbonate velocity was observed in only portions of two data sets, when mineralogy was explicitly considered and robust models that accounted for inclusion (pore) shape were used. Results from this analysis resulted in a recommended workflow, including a rock-physics template and dry-rock modulus diagnostics, for the evaluation of lab-based carbonate rock-physics data. The workflow was amenable to further integration with well-based data and other core-based petrophysical measurements (e.g., electrical properties).

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Upscaling of elastic properties in carbonates: A modeling approach based on a multiscale geophysical data set

10.5194/egusphere-egu2020-18106 ◽

2020 ◽

Author(s):

Jerome Fortin ◽

Cedric Bailly ◽

Mathilde Adelinet ◽

Youri Hamon

Keyword(s):

Elastic Properties ◽

Wave Velocity ◽

Representative Elementary Volume ◽

P Wave ◽

Elementary Volume ◽

Data Set ◽

Wave Velocities ◽

P Wave Velocity ◽

Ultrasonic Measurements ◽

Seismic Scale

Linking ultrasonic measurements made on samples, with sonic logs and seismic subsurface data, is a key challenge for the understanding of carbonate reservoirs. To deal with this problem, we investigate the elastic properties of dry lacustrine carbonates. At one study site, we perform a seismic refraction survey (100 Hz), as well as sonic (54 kHz) and ultrasonic (250 kHz) measurements directly on outcrop and ultrasonic measurements on samples (500 kHz). By comparing the median of each data set, we show that the P wave velocity decreases from laboratory to seismic scale. Nevertheless, the median of the sonic measurements acquired on outcrop surfaces seems to fit with the seismic data, meaning that sonic acquisition may be representative of seismic scale. To explain the variations due to upscaling, we relate the concept of representative elementary volume with the wavelength of each scale of study. Indeed, with upscaling, the wavelength varies from millimetric to pluri-metric. This change of scale allows us to conclude that the behavior of P wave velocity is due to different geological features (matrix porosity, cracks, and fractures) related to the different wavelengths used. Based on effective medium theory, we quantify the pore aspect ratio at sample scale and the crack/fracture density at outcrop and seismic scales using a multiscale representative elementary volume concept. Results show that the matrix porosity that controls the ultrasonic P wave velocities is progressively lost with upscaling, implying that crack and fracture porosity impacts sonic and seismic P wave velocities, a result of paramount importance for seismic interpretation based on deterministic approaches.Bailly, C., Fortin, J., Adelinet, M., & Hamon, Y. (2019). Upscaling of elastic properties in carbonates: A modeling approach based on a multiscale geophysical data set. Journal of Geophysical Research: Solid Earth, 124. https://doi.org/10.1029/2019JB018391

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Common-focus point-based target-oriented imaging approach for continuous seismic reservoir monitoring

Geophysics ◽

10.1190/geo2017-0842.1 ◽

2018 ◽

Vol 83 (4) ◽

pp. M41-M48 ◽

Cited By ~ 3

Author(s):

Hongwei Liu ◽

Mustafa Naser Al-Ali

Keyword(s):

Seismic Data ◽

Rock Physics ◽

Time Lapse ◽

Velocity Estimation ◽

Estimation Methods ◽

Data Sets ◽

Data Set ◽

Velocity Models ◽

Reservoir Monitoring ◽

Focus Point

The ideal approach for continuous reservoir monitoring allows generation of fast and accurate images to cope with the massive data sets acquired for such a task. Conventionally, rigorous depth-oriented velocity-estimation methods are performed to produce sufficiently accurate velocity models. Unlike the traditional way, the target-oriented imaging technology based on the common-focus point (CFP) theory can be an alternative for continuous reservoir monitoring. The solution is based on a robust data-driven iterative operator updating strategy without deriving a detailed velocity model. The same focusing operator is applied on successive 3D seismic data sets for the first time to generate efficient and accurate 4D target-oriented seismic stacked images from time-lapse field seismic data sets acquired in a [Formula: see text] injection project in Saudi Arabia. Using the focusing operator, target-oriented prestack angle domain common-image gathers (ADCIGs) could be derived to perform amplitude-versus-angle analysis. To preserve the amplitude information in the ADCIGs, an amplitude-balancing factor is applied by embedding a synthetic data set using the real acquisition geometry to remove the geometry imprint artifact. Applying the CFP-based target-oriented imaging to time-lapse data sets revealed changes at the reservoir level in the poststack and prestack time-lapse signals, which is consistent with the [Formula: see text] injection history and rock physics.

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Convolutional neural network for seismic impedance inversion

Geophysics ◽

10.1190/geo2018-0838.1 ◽

2019 ◽

Vol 84 (6) ◽

pp. R869-R880 ◽

Cited By ~ 11

Author(s):

Vishal Das ◽

Ahinoam Pollack ◽

Uri Wollner ◽

Tapan Mukerji

Keyword(s):

Rock Physics ◽

Normal Incidence ◽

Wave Impedance ◽

Training Data ◽

P Wave ◽

Computation Method ◽

Elastic Model ◽

Spatial Correlations ◽

Data Set ◽

Earth Models

We have addressed the geophysical problem of obtaining an elastic model of the subsurface from recorded normal-incidence seismic data using convolutional neural networks (CNNs). We train the network on synthetic full-waveform seismograms generated using Kennett’s reflectivity method on earth models that were created under rock-physics modeling constraints. We use an approximate Bayesian computation method to estimate the posterior distribution corresponding to the CNN prediction and to quantify the uncertainty related to the predictions. In addition, we test the robustness of the network in predicting impedances of previously unobserved earth models when the input to the network consisted of seismograms generated using: (1) earth models with different spatial correlations (i.e. variograms), (2) earth models with different facies proportions, (3) earth models with different underlying rock-physics relations, and (4) source-wavelet phase and frequency different than in the training data. Results indicate that the predictions of the trained network are susceptible to facies proportions, the rock-physics model, and source-wavelet parameters used in the training data set. Finally, we apply CNN inversion on the Volve field data set from offshore Norway. P-wave impedance [Formula: see text] inverted for the Volve data set using CNN showed a strong correlation (82%) with the [Formula: see text] log at a well.

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Elastic reflectivity vectors and the geometry of intercept-gradient crossplots

The Leading Edge ◽

10.1190/tle38100762.1 ◽

2019 ◽

Vol 38 (10) ◽

pp. 762-769

Author(s):

Patrick Connolly

Keyword(s):

Elastic Property ◽

Elastic Properties ◽

Wave Velocity ◽

Seismic Data ◽

Measurement Errors ◽

Rock Physics ◽

P Wave ◽

S Wave ◽

P Wave Velocity ◽

Well Log Analysis

Reflectivities of elastic properties can be expressed as a sum of the reflectivities of P-wave velocity, S-wave velocity, and density, as can the amplitude-variation-with-offset (AVO) parameters, intercept, gradient, and curvature. This common format allows elastic property reflectivities to be expressed as a sum of AVO parameters. Most AVO studies are conducted using a two-term approximation, so it is helpful to reduce the three-term expressions for elastic reflectivities to two by assuming a relationship between P-wave velocity and density. Reduced to two AVO components, elastic property reflectivities can be represented as vectors on intercept-gradient crossplots. Normalizing the lengths of the vectors allows them to serve as basis vectors such that the position of any point in intercept-gradient space can be inferred directly from changes in elastic properties. This provides a direct link between properties commonly used in rock physics and attributes that can be measured from seismic data. The theory is best exploited by constructing new seismic data sets from combinations of intercept and gradient data at various projection angles. Elastic property reflectivity theory can be transferred to the impedance domain to aid in the analysis of well data to help inform the choice of projection angles. Because of the effects of gradient measurement errors, seismic projection angles are unlikely to be the same as theoretical angles or angles derived from well-log analysis, so seismic data will need to be scanned through a range of angles to find the optimum.

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Inversion of multicomponent, multiazimuth, walkaway VSP data for the stiffness tensor

Geophysics ◽

10.1190/1.1581073 ◽

2003 ◽

Vol 68 (3) ◽

pp. 1022-1031 ◽

Cited By ~ 44

Author(s):

Pawan Dewangan ◽

Vladimir Grechka

Keyword(s):

Elastic Stiffness ◽

P Wave ◽

Vacuum Field ◽

Stiffness Tensor ◽

Slowness Surface ◽

Data Set ◽

S Waves ◽

Stiffness Coefficients ◽

Vsp Data ◽

Walkaway Vsp

Vertical seismic profiling (VSP), an established technique, can be used for estimating in‐situ anisotropy that might provide valuable information for characterization of reservoir lithology, fractures, and fluids. The P‐wave slowness components, conventionally measured in multiazimuth, walkaway VSP surveys, allow one to reconstruct some portion of the corresponding slowness surface. A major limitation of this technique is that the P‐wave slowness surface alone does not constrain a number of stiffness coefficients that may be crucial for inferring certain rock properties. Those stiffnesses can be obtained only by combining the measurements of P‐waves with those of S (or PS) modes. Here, we extend the idea of Horne and Leaney, who proved the feasibility of joint inversion of the slowness and polarization vectors of P‐ and SV‐waves for parameters of transversely isotropic media with a vertical symmetry axis (VTI symmetry). We show that there is no need to assume a priori VTI symmetry or any other specific type of anisotropy. Given a sufficient polar and azimuthal coverage of the data, the polarizations and slownesses of P and two split shear (S1 and S2) waves are sufficient for estimating all 21 elastic stiffness coefficients cij that characterize the most general triclinic anisotropy. The inverted stiffnesses themselves indicate whether or not the data can be described by a higher‐symmetry model. We discuss three different scenarios of inverting noise‐contaminated data. First, we assume that the layers are horizontal and laterally homogeneous so that the horizontal slownesses measured at the surface are preserved at the receiver locations. This leads to a linear inversion scheme for the elastic stiffness tensor c. Second, if the S‐wave horizontal slowness at the receiver location is unknown, the elastic tensor c can be estimated in a nonlinear fashion simultaneously with obtaining the horizontal slowness components of S‐waves. The third scenario includes the nonlinear inversion for c using only the vertical slowness components and the polarization vectors of P‐ and S‐waves. We find the inversion to be stable and robust for the first and second scenarios. In contrast, errors in the estimated stiffnesses increase substantially when the horizontal slowness components of both P‐ and S‐waves are unknown. We apply our methodology to a multiazimuth, multicomponent VSP data set acquired in Vacuum field, New Mexico, and show that the medium at the receiver level can be approximated by an azimuthally rotated orthorhombic model.

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Mineral lithotype identification on the andrill AND-2A drillcore, antarctica by using ternary mineral rock physics templates built from a self-consistent approach

Geofísica Internacional ◽

10.22201/igeof.00167169p.2022.61.1.2126 ◽

2022 ◽

Vol 61 (1) ◽

pp. 40-54

Author(s):

Jaime Meléndez Martínez ◽

Rubén Nicolás López ◽

Oscar C Valdiviezo

Keyword(s):

Elastic Properties ◽

Visual Analysis ◽

Rock Physics ◽

Compressional Wave ◽

Data Sets ◽

Log Data ◽

Additional Information ◽

Property Data ◽

Self Consistent ◽

Drill Holes

In this work, wet bulk density ?WBD and compressional wave velocity VP core log data obtained along the AND-2A drillcore are plotted on density-velocity ternary mineral Rock Physics Templates (RPTs) built from a Self-Consistent (SC) micromechanics modelling with the purpose to deter- mine data trends that allow us to assist in identifying mineral lithotypes and lithological features throughout the 1138 m length of the drillcore. The elastic properties of the three dominant miner- als present in the drillcore (mixed clays, quartz, and calcite) and the pore-filling fluid (brine) were used as input data for the SC model. The interpreted lithology is then compared to that obtained from the analysis of the AND-2A drillcore ?WBD and VP log data using Gardner type density-velocity cross plots. Results from both the SC and Gardner methods are in good agreement with the main lithologies present in the AND-2A drillcore already reported in the scientific literature. Our findings also agree well when compared to the lithological description of six selected rock samples obtained at different depths on the AND-2A drillcore. These results suggest that the proposed SC approach could be helpful to assist to identify lithology in scientific drill holes where downhole elastic proper- ties may exist over intervals where portions of the drillcore were not recovered. Furthermore, even when elastic property data sets come from measurements on cores, the SC approach is likewise useful because, from visual analysis alone, lithology can sometimes be difficult to determine, and additional information from the analysis of the elastic properties may provide more insight.

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Elastic properties of rock salt: Laboratory measurements and Gulf of Mexico well-log analysis

Geophysics ◽

10.1190/geo2016-0527.1 ◽

2017 ◽

Vol 82 (5) ◽

pp. D303-D317 ◽

Cited By ~ 9

Author(s):

Jingjing Zong ◽

Robert R. Stewart ◽

Nikolay Dyaur ◽

Michael T. Myers

Keyword(s):

Gulf Of Mexico ◽

Elastic Properties ◽

Rock Salt ◽

Model Building ◽

Complex Geometry ◽

Rock Physics ◽

P Wave ◽

Elastic Behavior ◽

Laboratory Measurements ◽

Wave Velocities

Rock salt (essentially halite) is a special type of sedimentary rock that has played a large role throughout tectonic and economic history. The unique physical properties of halite (ductility, low density, flowability, and impermeability) can be critical factors in hydrocarbon traps and underground storage. However, seismic imaging and interpretation can be challenging when salt structures are present due to their complex geometry and large impedance contrasts relative to surrounding rocks. To investigate the properties of rock salt in terms of elastic parameters, we use ultrasonic laboratory measurements and well logs. In the laboratory, we have analyzed the effects of composition, crystalline structure, pressure, and temperature on the elastic behavior of a variety of rock salt samples. The samples include pure halite (>95 wt%) from the Gulf of Mexico (GOM) area, argillaceous rock salt from the Zipaquirá Mine, Colombia, and crystalline salt from the Goderich Mine, Canada. Current measurements suggest that the GOM salt cores behave isotropically in general. The Zipaquirá salt samples show velocity and density variations on account of their heterogeneous composition. The Goderich halite crystals display distinct cubic anisotropy. Measurements on the GOM samples at varying confining pressures and temperatures indicate that increasing pressure elevates velocity whereas increasing temperature decreases velocity. From the analysis of 145 log suites from boreholes drilled through rock salt in the northern GOM, we found that, within the salt formations, P-wave velocities increased slightly with depth (approximately [Formula: see text] per km). The S-wave velocities from three wells range from 2280 to [Formula: see text]. Bulk densities from all the wells cluster at [Formula: see text]. These laboratory and log measurements provide new values for the elastic properties of rock salt, which can assist in velocity model building, synthetic seismogram generation, and the understanding of the rock physics of halite.

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Analisis Model Kecepatan Gelombang-P pada Coal-Seam Gas Studi Kasus Cekungan Sumatera Selatan, Indonesia

Jurnal Geofisika Eksplorasi ◽

10.23960/jge.v6i2.74 ◽

2020 ◽

Vol 6 (2) ◽

pp. 113-120

Author(s):

Harnanti Yogaputri Hutami ◽

Fitriyani Fitriyani ◽

Tiara Larasati Priniarti ◽

Handoyo Handoyo

Keyword(s):

Coal Seam ◽

Elastic Properties ◽

Wave Velocity ◽

Rock Physics ◽

Velocity Model ◽

Significant Negative Correlation ◽

P Wave ◽

Gas Content ◽

Coal Seam Gas ◽

P Wave Velocity

The rock physics model is one effective yet challenging way to investigate the coal-seam gas potential in Indonesia. However, because of the complex conditions of the Coal-Seam Gas Reservoirs, it is difficult to establish models. Despite the scarce modeling, this study aims to estimate the relation of gas-saturated within pores of coal seam to the elastic properties of rock, which is P-wave velocity. First, the coal seam minerals are applied to quantify matrix moduli using the Voigt-Reuss-Hill Average method. Pride’s simple equation is used to estimate the elastic properties of the coal seam at dry condition (zero gas saturation). Finally, Biot-Gassmann’s theory is applied to determine the elastic properties of coal seam with fully gas saturated. As the result, the proposed model showed that there is a significant negative correlation between gas content with both density and P-wave velocity of the coal seam. Finally, this P-wave velocity model of gas-saturated coal seams should be properly useful as the quick look for identifying coal seam gas potentials.

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On the influence and limitations of hyper-resolution hydrological modelling – application of the 1 km PCR-GLOBWB model over Europe

10.5194/egusphere-egu21-125 ◽

2021 ◽

Author(s):

Jannis Hoch ◽

Edwin Sutanudjaja ◽

Rens van Beek ◽

Marc Bierkens

Keyword(s):

Global Scale ◽

Data Sets ◽

The Novel ◽

Data Set ◽

Meteorological Forcing ◽

Recent Developments ◽

Terrestrial Water ◽

Multiple Challenges ◽

Global Data ◽

Development Application

Developing and applying hyper-resolution models over larger extents has long been a quest in hydrological sciences. With the recent developments of global-scale yet fine data sets and advances in computational power, achieving this goal becomes increasingly feasible.We here present the development, application, and results of the novel 1 km version of PCR-GLOBWB for the period 1981 until 2020. Even though employing global data sets only, we developed, ran, and evaluated the 1 km model for the continent Europe only. In comparison to past versions of PCR-GLOBWB, input data was replaced with sufficiently fine data, for example the recent SoilGrids and MERIT-DEM data. Preliminary results indicate an improvement of model outcome when evaluating simulated discharge, evaporation, and terrestrial water storage.Additionally, we aim to answer the question to what extent developing hyper-resolution models is actually needed of whether the run times could be saved by using hyper-resolution state-of-the-art meteorological forcing. Therefore, the relative importance of model resolution and forcing resolution was cross-compared. To that end, the ERA5-Land data set was employed at different resolutions, matching the model resolutions at 1 km, 10 km, and 50 km.Despite multiple challenges still lying ahead before achieve true hyper-resolution, this application of a 1 km model across an entire continent can form the basis for the next steps to be taken.

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Near-real-time adjusted reanalysis forcing data for hydrology

Hydrology and Earth System Sciences ◽

10.5194/hess-22-989-2018 ◽

2018 ◽

Vol 22 (2) ◽

pp. 989-1000 ◽

Cited By ~ 18

Author(s):

Peter Berg ◽

Chantal Donnelly ◽

David Gustafsson

Keyword(s):

Real Time ◽

Global Scale ◽

Reanalysis Data ◽

The Arctic ◽

Data Sets ◽

Initial State ◽

Time Step ◽

Data Set ◽

Global Data Sets ◽

Global Data

Abstract. Extending climatological forcing data to current and real-time forcing is a necessary task for hydrological forecasting. While such data are often readily available nationally, it is harder to find fit-for-purpose global data sets that span long climatological periods through to near-real time. Hydrological simulations are generally sensitive to bias in the meteorological forcing data, especially relative to the data used for the calibration of the model. The lack of high-quality daily resolution data on a global scale has previously been solved by adjusting reanalysis data with global gridded observations. However, existing data sets of this type have been produced for a fixed past time period determined by the main global observational data sets. Long delays between updates of these data sets leaves a data gap between the present day and the end of the data set. Further, hydrological forecasts require initializations of the current state of the snow, soil and lake (and sometimes river) storage. This is normally conceived by forcing the model with observed meteorological conditions for an extended spin-up period, typically at a daily time step, to calculate the initial state. Here, we present and evaluate a method named HydroGFD (Hydrological Global Forcing Data) to combine different data sets in order to produce near-real-time updated hydrological forcing data of temperature and precipitation that are compatible with the products covering the climatological period. HydroGFD resembles the already established WFDEI (WATCH Forcing Data–ERA-Interim) method (Weedon et al., 2014) closely but uses updated climatological observations, and for the near-real time it uses interim products that apply similar methods. This allows HydroGFD to produce updated forcing data including the previous calendar month around the 10th of each month. We present the HydroGFD method and therewith produced data sets, which are evaluated against global data sets, as well as with hydrological simulations with the HYPE (Hydrological Predictions for the Environment) model over Europe and the Arctic regions. We show that HydroGFD performs similarly to WFDEI and that the updated period significantly reduces the bias of the reanalysis data. For real-time updates until the current day, extending HydroGFD with operational meteorological forecasts, a large drift is present in the hydrological simulations due to the bias of the meteorological forecasting model.

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