Fluid substitution for thinly interbedded sand-shale sequences using the mesh method

Geophysics ◽  
2016 ◽  
Vol 81 (6) ◽  
pp. D599-D609 ◽  
Author(s):  
Piyapa Dejtrakulwong ◽  
Gary Mavko
Keyword(s):  
Pore Space ◽  
Linear Trend ◽  
Rock Physics ◽  
Normal Incidence ◽  
Effective Porosity ◽  
P Wave ◽  
Measurement Scale ◽  
Fluid Substitution ◽  
Conventional Procedure ◽  
Substitution Procedure

Gassmann’s fluid substitution model is intended for a monomineralic, homogeneous porous rock, in which pore pressures induced by applied loads can equilibrate throughout the pore space. These assumptions are violated when Gassmann’s equations are applied to measurements that represent effective medium averages over subresolution layers of alternating sand and shale. The conventional procedure for treating this problem has been to first downscale; i.e., estimate the properties of the fine-scale sand and shale endmembers from the coarse-scale measurements, apply Gassmann’s fluid substitution to the sand only, and then Backus average back to the original scale. This procedure, however, is very sensitive to errors in estimated sand fraction and shale properties and becomes particularly unstable at small sand fractions. A new method for fluid substitution combines rock-physics models for dispersed and interbedded sand-shale systems, which are often approximated with Reuss or lower Hashin-Shtrikman interpolations between endmembers quartz mineral, clean sand, and shale. When expressed as P-wave compliance versus porosity, these trends become approximately linear. The Backus average of the normal incidence P-wave compliance of thinly layered mixtures of various sand-shale facies is also a linear trend with porosity. As a result, the upscaled fluid substitution change of compliance of any point within the dispersed or layered sand-shale system is approximately proportional to the fluid-substituted change of compliance of the clean sand endmember, scaled by the ratio of effective porosity to clean sand porosity. The result is a fluid substitution procedure that operates directly at the measurement scale, without the need to downscale the measurements, while still changing fluid in the sand layers only.

Convolutional neural network for seismic impedance inversion

Geophysics ◽  
2019 ◽  
Vol 84 (6) ◽  
pp. R869-R880 ◽  
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.

Petroacoustics and composition of presalt rocks from Santos Basin

2019 ◽  
Vol 38 (5) ◽  
pp. 342-348 ◽  
Author(s):  
Guilherme Fernandes Vasquez ◽  
Marcio José Morschbacher ◽  
Camila Wense Dias dos Anjos ◽  
Yaro Moisés Parisek Silva ◽  
Vanessa Madrucci ◽  
...  
Keyword(s):  
Clay Minerals ◽  
Chemical Elements ◽  
Pore Space ◽  
Rock Physics ◽  
P Wave ◽  
Rock Properties ◽  
Tectonic Activity ◽  
S Wave ◽  
Wave Velocities ◽  
Lacustrine Carbonate

The deposition of the presalt section from Santos Basin began when Gondwana started to break up and South America and Africa were separating. Initial synrift carbonate deposits affected by relatively severe tectonic activity evolved to a lacustrine carbonate environment during the later stages of basin formation. Although the reservoirs are composed of carbonate rocks, the occurrence of faults and the intense colocation of igneous rocks served as a source of chemical elements uncommon in typical carbonate environments. Consequently, beyond the presence of different facies with complex textures and pore geometries, the presalt reservoir rocks present marked compositional and microstructural variability. Therefore, rock-physics modeling is used to understand and interpret the extensive laboratory measurements of P-wave velocities, S-wave velocities, and density that we have undertaken on the presalt carbonate cores from Santos Basin. We show that quartz and exotic clay minerals (such as stevensite and other magnesium-rich clay minerals), which have different values of elastic moduli and Poisson's ratio as compared to calcite and dolomite, may introduce noticeable “Poisson's reflectivity anomalies” on prestack seismic data. Moreover, although the authors concentrate their attention on composition, it will become clear that pore-space geometry also may influence seismic rock properties of presalt carbonate reservoirs.

Sediments with gas hydrates: Internal structure from seismic AVO

Geophysics ◽  
1998 ◽  
Vol 63 (5) ◽  
pp. 1659-1669 ◽  
Author(s):  
Christine Ecker ◽  
Jack Dvorkin ◽  
Amos Nur
Keyword(s):  
Internal Structure ◽  
Wave Velocity ◽  
Seismic Data ◽  
Pore Space ◽  
Rock Physics ◽  
P Wave ◽  
S Wave ◽  
High Concentration ◽  
Amplitude Variation With Offset ◽  
Bottom Simulating Reflector

We interpret amplitude variation with offset (AVO) data from a bottom simulating reflector (BSR) offshore Florida by using rock‐physics‐based synthetic seismic models. A previously conducted velocity and AVO analysis of the in‐situ seismic data showed that the BSR separates hydrate‐bearing sediments from sediments containing free methane. The amplitude at the BSR are increasingly negative with increasing offset. This behavior was explained by P-wave velocity above the BSR being larger than that below the BSR, and S-wave velocity above the BSR being smaller than that below the BSR. We use these AVO and velocity results to infer the internal structure of the hydrated sediment. To do so, we examine two micromechanical models that correspond to the two extreme cases of hydrate deposition in the pore space: (1) the hydrate cements grain contacts and strongly reinforces the sediment, and (2) the hydrate is located away from grain contacts and does not affect the stiffness of the sediment frame. Only the second model can qualitatively reproduce the observed AVO response. Thus inferred internal structure of the hydrate‐bearing sediment means that (1) the sediment above the BSR is uncemented and, thereby, mechanically weak, and (2) its permeability is very low because the hydrate clogs large pore‐space conduits. The latter explains why free gas is trapped underneath the BSR. The seismic data also indicate the absence of strong reflections at the top of the hydrate layer. This fact suggests that the high concentration of hydrates in the sediment just above the BSR gradually decreases with decreasing depth. This effect is consistent with the fact that the low‐permeability hydrated sediments above the BSR prevent free methane from migrating upwards.

Viscoelasticity of Ells River bitumen sand and 4D monitoring of thermal enhanced oil recovery processes

Geophysics ◽  
2013 ◽  
Vol 78 (6) ◽  
pp. D419-D428 ◽  
Author(s):  
James W. Spencer
Keyword(s):  
Bulk Modulus ◽  
Enhanced Oil Recovery ◽  
Oil Recovery ◽  
Pore Space ◽  
Rock Physics ◽  
Steam Injection ◽  
P Wave ◽  
Low Frequencies ◽  
Recovery Processes ◽  
Seismic Frequencies

Samples of Ells River bitumen sand from Alberta, Canada were measured at low frequencies (0.2–205 Hz) to determine the temperature and frequency dependence of velocities and attenuations. The samples were first measured “as received” where the pore space is mostly filled with bitumen but also contains small amounts of air and water. With residual air in the pores, at 5°C, there is strong dispersion in the P-wave modulus and a peak in attenuation at seismic frequencies. The frequency-dependent moduli and attenuations shift by three orders of magnitude in frequency as temperature is increased from 5°C to 48°C, consistent with the bitumen viscosity. Samples were then saturated so any empty pore space is filled with water. After saturation, at 1 Hz, increasing temperature from 5°C to 49°C causes a 30% reduction in the saturated P-wave modulus, a 34% reduction in the saturated bulk modulus, and a 6% reduction in the shear modulus. This behavior can only be explained by the temperature-dependent bulk modulus of bitumen. The results enable predictions regarding the P-velocities that can be expected during seismic monitoring of thermal enhanced oil recovery processes. Velocities for cold bitumen sand are near [Formula: see text] at reservoir pressure and temperature. Following steam injection, velocities should be very low (near [Formula: see text]) in heated zones more than 50°C with a free gas phase, which could be steam or gas. There will be a progressive reduction in velocities, i.e., [Formula: see text] at 25°C and [Formula: see text] at 49°C, in areas of formation heating, but without steam or gas in the pores. Albeit smaller than the effect of steam, the effect of formation heating alone is large enough to be easily detected by today’s 4D surveys. With local rock physics calibration, it should be possible to map the areal extent of formation heating using 4D seismic data.

scholarly journals Identification of hydrocarbons in chalk reservoirs from surface seismic data: South Arne field, North Sea

2005 ◽  
Vol 7 ◽  
pp. 13-16
Author(s):  
Peter Japsen ◽  
Anders Bruun ◽  
Ida L. Fabricius ◽  
Gary Mavko
Keyword(s):  
Wave Velocity ◽  
North Sea ◽  
Seismic Data ◽  
Pore Space ◽  
Sedimentary Rocks ◽  
Rock Physics ◽  
Acoustic Properties ◽  
P Wave ◽  
S Wave ◽  
Reservoir Rocks

Seismic data are mainly used to map out structures in the subsurface, but are also increasingly used to detect differences in porosity and in the fluids that occupy the pore space in sedimentary rocks. Hydrocarbons are generally lighter than brine, and the bulk density and sonic velocity (speed of pressure waves or P-wave velocity) of hydrocarbon-bearing sedimentary rocks are therefore reduced compared to non-reservoir rocks. However, sound is transmitted in different wave forms through the rock, and the shear velocity (speed of shear waves or S-wave velocity) is hardly affected by the density of the pore fluid. In order to detect the presence of hydrocarbons from seismic data, it is thus necessary to investigate how porosity and pore fluids affect the acoustic properties of a sedimentary rock. Much previous research has focused on describing such effects in sandstone (see Mavko et al. 1998), and only in recent years have corresponding studies on the rock physics of chalk appeared (e.g. Walls et al. 1998; Røgen 2002; Fabricius 2003; Gommesen 2003; Japsen et al. 2004). In the North Sea, chalk of the Danian Ekofisk Formation and the Maastrichtian Tor Formation are important reservoir rocks. More information could no doubt be extracted from seismic data if the fundamental physical properties of chalk were better understood. The presence of gas in chalk is known to cause a phase reversal in the seismic signal (Megson 1992), but the presence of oil in chalk has only recently been demonstrated to have an effect on surface seismic data (Japsen et al. 2004). The need for a better link between chalk reservoir parameters and geophysical observations has, however, strongly increased since the discovery of the Halfdan field proved major reserves outside four-way dip closures (Jacobsen et al. 1999; Vejbæk & Kristensen 2000).

scholarly journals Rock property modelling and sensitivity analysis for hydrocarbon exploration in OSSY field, Niger Delta Basin

2021 ◽  
Vol 11 (4) ◽  
pp. 1809-1822
Author(s):  
Alexander Ogbamikhumi ◽  
Osakpolor Marvellous Omorogieva
Keyword(s):  
Wave Velocity ◽  
Structural Complexity ◽  
Rock Physics ◽  
Hydrocarbon Exploration ◽  
P Wave ◽  
Rock Properties ◽  
Fluid Substitution ◽  
Quantitative Interpretation ◽  
S Wave ◽  
Reflection Pattern

AbstractThe application of quantitative interpretation techniques for hydrocarbon prospect evaluation from seismic has become so vital. The effective employment of these techniques is dependent on several factors: the quality of the seismic and well data, sparseness of data, the physics of rock, lithological and structural complexity of the field. This study adopts reflection pattern, amplitude versus offset (AVO), Biot–Gassmann fluid substitution and cross-plot models to understand the physics of the reservoir rocks in the field by examining the sensitivity of the basic rock properties; P-wave velocity, S-wave velocity and density, to variation in lithology and fluid types in the pore spaces of reservoirs. This is to ascertain the applicability of quantitative seismic interpretation techniques to explore hydrocarbon prospect in the studied field. The results of reflection pattern and AVO models revealed that the depth of interest is dominated by Class IV AVO sands with a high negative zero offset reflectivity that reduces with offset. The AVO intercept versus gradient plot indicated that both brine and hydrocarbon bearing sands can be discriminated on seismic. Fluid substitution modelling results revealed that the rock properties will favourably respond to variation in oil saturation, but as little as 5% gas presence will result in huge change in the rock properties, which will remain constant upon further increments of gas saturation, thereby making it difficult to differentiate between economical and sub-economical saturations of gas on seismic data. Rock physics cross-plot models revealed separate cluster points typical of shale presence, brine sands and hydrocarbon bearing sands. Thus, the response of the rock properties to the modelling processes adopted favours the application of quantitative interpretation techniques to evaluate hydrocarbon in the field.

scholarly journals Fluid substitution in shaley sediment using effective porosity

Geophysics ◽  
2007 ◽  
Vol 72 (3) ◽  
pp. O1-O8 ◽  
Author(s):  
Jack Dvorkin ◽  
Gary Mavko ◽  
Boris Gurevich
Keyword(s):  
Elastic Modulus ◽  
Pore Space ◽  
Total Porosity ◽  
Effective Porosity ◽  
Fluid Substitution ◽  
Mineral Phase ◽  
Hydrocarbon Production ◽  
System A ◽  
Alternative Method ◽  
Water Saturated

The traditional method of fluid substitution in porous rock requires the total porosity and the elastic modulus of the mineral phase as input and assumes that the fluid reaches instantaneous hydraulic equilibrium throughout the pore space. This assumption may not be appropriate for shaley sediment because of the low permeability of shale and the resulting immobility of the water in it. To address this problem, we propose an alternative method that uses effective porosity instead of total porosity. Effective porosity is lower than total porosity if porous shale is present in the system. A new, composite mineral phase is introduced, which includes the porous water-saturated shale together with the nonporous minerals and whose elastic modulus is an average of those of its components, including the porous shale. This alternative method increases the sensitivity of the elastic properties of sediment-to-pore-fluid changes and therefore may be used as a physics-based theoretical tool to better explain and interpret seismic data during exploration as well as variations in seismic response as hydrocarbon production progresses.

Permeability-porosity transforms from small sandstone fragments

Geophysics ◽  
2006 ◽  
Vol 71 (1) ◽  
pp. N11-N19 ◽  
Author(s):  
Ayako Kameda ◽  
Jack Dvorkin ◽  
Youngseuk Keehm ◽  
Amos Nur ◽  
William Bosl
Keyword(s):  
Pore Space ◽  
Petroleum Industry ◽  
Rock Physics ◽  
Three Dimensions ◽  
Absolute Permeability ◽  
High Porosity ◽  
Drill Cuttings ◽  
Thin Sections ◽  
Numerical Experimentation ◽  
The Absolute

Numerical simulation of laboratory experiments on rocks, or digital rock physics, is an emerging field that may eventually benefit the petroleum industry. For numerical experimentation to find its way into the mainstream, it must be practical and easily repeatable — i.e., implemented on standard hardware and in real time. This condition reduces the size of a digital sample to just a few grains across. Also, small physical fragments of rock, such as cuttings, may be the only material available to produce digital images. Will the results be meaningful for a larger rock volume? To address this question, we use a number of natural and artificial medium- to high-porosity, well-sorted sandstones. The 3D microtomography volumes are obtained from each physical sample. Then, analogous to making thin sections of drill cuttings, we select a large number of small 2D slices from a 3D scan. As a result, a single physical sample produces hundreds of 2D virtual-drill-cuttings images. Corresponding 3D pore-space realizations are generated statistically from these 2D images; fluid flow is simulated in three dimensions, and the absolute permeability is computed. The results show that small fragments of medium– to high-porosity sandstones that are statistically subrepresentative of a larger sample will not yield the exact porosity and permeability of the sample. However, a significant number of small fragments will yield a site-specific permeability-porosity trend that can then be used to estimate the absolute permeability from independent porosity data obtained in the well or inferred from seismic techniques.

Characterization of elastic properties of near-surface and subsurface deepwater hydrate-bearing sediments

Geophysics ◽  
2013 ◽  
Vol 78 (3) ◽  
pp. D169-D179 ◽  
Author(s):  
Zijian Zhang ◽  
De-hua Han ◽  
Daniel R. McConnell
Keyword(s):  
Wave Velocity ◽  
Elastic Constants ◽  
Gas Hydrate ◽  
Effective Medium Theory ◽  
Pore Space ◽  
Seismic Interpretation ◽  
P Wave ◽  
Near Surface ◽  
Free Gas ◽  
Hydrate Bearing Sediments

Hydrate-bearing sands and shallow nodular hydrate are potential energy resources and geohazards, and they both need to be better understood and identified. Therefore, it is useful to develop methodologies for modeling and simulating elastic constants of these hydrate-bearing sediments. A gas-hydrate rock-physics model based on the effective medium theory was successfully applied to dry rock, water-saturated rock, and hydrate-bearing rock. The model was used to investigate the seismic interpretation capability of hydrate-bearing sediments in the Gulf of Mexico by computing elastic constants, also known as seismic attributes, in terms of seismic interpretation, including the normal incident reflectivity (NI), Poisson’s ratio (PR), P-wave velocity ([Formula: see text]), S-wave velocity ([Formula: see text]), and density. The study of the model was concerned with the formation of gas hydrate, and, therefore, hydrate-bearing sediments were divided into hydrate-bearing sands, hydrate-bearing sands with free gas in the pore space, and shallow nodular hydrate. Although relations of hydrate saturation versus [Formula: see text] and [Formula: see text] are different between structures I and II gas hydrates, highly concentrated hydrate-bearing sands may be interpreted on poststack seismic amplitude sections because of the high NI present. The computations of elastic constant implied that hydrate-bearing sands with free gas could be detected with the crossplot of NI and PR from prestack amplitude analysis, and density may be a good hydrate indicator for shallow nodular hydrate, if it can be accurately estimated by seismic methods.

Multi-Mineral Segmentation of SEM Images Using Deep Learning Techniques

2021 ◽  
Author(s):  
Vladislav Vasilevich Alekseev ◽  
Denis Mihaylovich Orlov ◽  
Dmitry Anatolevich Koroteev
Keyword(s):  
Neural Networks ◽  
Deep Learning ◽  
Deep Neural Networks ◽  
Pore Space ◽  
Rock Physics ◽  
Sem Images ◽  
Digital Rock Physics ◽  
Learning Techniques ◽  
Digital Core ◽  
Non Destructive

Abstract The approaches of building and methods of using the digital core are currently developing rapidly. The use of these methods makes it possible to obtain petrophysical information by non-destructive methods quickly. Digital rock physics includes two main stages: constructing models and modeling various physical processes on the obtained models. Our work proposes using deep learning methods for mineral and pore space segmentation instead of classical methods such as threshold image processing. Deep neural networks have long been able to show their advantages in many areas of computer vision. This paper proposes and tests methods that help identify different minerals in images from a scanning electron microscope. We used images of rocks of the Achimov formation, which are arkoses, as samples. We tested various deep neural networks such as LinkNet, U-Net, ResUNet, and pix2pix and identified those that performed best in segmentation.

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