Relevant bibliographies by topics / Rock physics

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Rock physics'

Author: Grafiati
Published: 4 June 2021
Last updated: 8 June 2024

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Journal articles on the topic "Rock physics"

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Li, Yongyi, Lev Vernik, Mark Chapman, and Joel Sarout. "Introduction to this special section: Rock physics." Leading Edge 38, no. 5 (May 2019): 332. http://dx.doi.org/10.1190/tle38050332.1.

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Rock physics links the physical properties of rocks to geophysical and petrophysical observations and, in the process, serves as a focal point in many exploration and reservoir characterization studies. Today, the field of rock physics and seismic petrophysics embraces new directions with diverse applications in estimating static and dynamic reservoir properties through time-variant mechanical, thermal, chemical, and geologic processes. Integration with new digital and computing technologies is gradually gaining traction. The use of rock physics in seismic imaging, prestack seismic analysis, seismic inversion, and geomechanical model building also contributes to the increase in rock-physics influence. This special section highlights current rock-physics research and practices in several key areas, namely experimental rock physics, rock-physics theory and model studies, and the use of rock physics in reservoir characterizations.
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Amato del Monte, Alessandro. "Seismic rock physics." Leading Edge 36, no. 6 (June 2017): 523–25. http://dx.doi.org/10.1190/tle36060523.1.

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Rock physics studies the relationship between physical and elastic properties of rocks and is the basis of quantitative seismic interpretation. It has arguably given exploration geophysicists a solid quantitative basis to their interpretation of seismic data. It can be tackled at different scales of investigation by people with various backgrounds — from geophysicists to civil engineers, from mathematicians to petrophysicists.
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Das, Agnibha, and Madhumita Sengupta. "Introduction to this special section: Rock physics." Leading Edge 40, no. 9 (September 2021): 644. http://dx.doi.org/10.1190/tle40090644.1.

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In simple terms, rock physics provides the much-needed link between measurable elastic properties of rocks and their intrinsic properties. This enables us to connect seismic data, well logs, and laboratory measurements to minerology, porosity, permeability, fluid saturations, and stress. Rock-physics relationships/models are used to understand seismic signatures in terms of reservoir properties that help in exploration risk mitigation. Traditionally, rock physics has played an irreplaceable role in amplitude variation with offset (AVO) modeling and inversion, 3D/4D close-the-loop studies, and seismic time-lapse analysis and interpretation. Today, rock-physics research and application have influenced a much wider space that spans digital rock physics, microseismic, and distributed acoustic sensing (DAS) data analysis. In this special section, we have included papers that cover much of these advanced methods, providing us with a better understanding of subsurface elastic and transport properties, thereby reducing bias and uncertainties in quantitative interpretation.
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Saenger, Erik H., Stephanie Vialle, Maxim Lebedev, David Uribe, Maria Osorno, Mandy Duda, and Holger Steeb. "Digital carbonate rock physics." Solid Earth 7, no. 4 (August 4, 2016): 1185–97. http://dx.doi.org/10.5194/se-7-1185-2016.

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Abstract. Modern estimation of rock properties combines imaging with advanced numerical simulations, an approach known as digital rock physics (DRP). In this paper we suggest a specific segmentation procedure of X-ray micro-computed tomography data with two different resolutions in the µm range for two sets of carbonate rock samples. These carbonates were already characterized in detail in a previous laboratory study which we complement with nanoindentation experiments (for local elastic properties). In a first step a non-local mean filter is applied to the raw image data. We then apply different thresholds to identify pores and solid phases. Because of a non-neglectable amount of unresolved microporosity (micritic phase) we also define intermediate threshold values for distinct phases. Based on this segmentation we determine porosity-dependent values for effective P- and S-wave velocities as well as for the intrinsic permeability. For effective velocities we confirm an observed two-phase trend reported in another study using a different carbonate data set. As an upscaling approach we use this two-phase trend as an effective medium approach to estimate the porosity-dependent elastic properties of the micritic phase for the low-resolution images. The porosity measured in the laboratory is then used to predict the effective rock properties from the observed trends for a comparison with experimental data. The two-phase trend can be regarded as an upper bound for elastic properties; the use of the two-phase trend for low-resolution images led to a good estimate for a lower bound of effective elastic properties. Anisotropy is observed for some of the considered subvolumes, but seems to be insignificant for the analysed rocks at the DRP scale. Because of the complexity of carbonates we suggest using DRP as a complementary tool for rock characterization in addition to classical experimental methods.
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Hunter, Sander, Ronny Hofmann, and Irene Espejo. "Integrating grain-scale geology in digital rock physics." Leading Edge 37, no. 6 (June 2018): 428–34. http://dx.doi.org/10.1190/tle37060428.1.

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Digital rock physics (DRP) is a rapidly evolving field of study. One component of digital rock that has not received sufficient attention is how well actual rocks are represented in DRP. Instead, the digital rock community is focused on characterizing the pore space in volumes of rock imaged by microcomputed tomography (micro-CT) and simulating flow through that digitized pore network. This enables computational simulations of routine core analysis measurements, which may be completed in hours instead of days or weeks. Although this alone makes digital rock a worthwhile endeavor, it overlooks much of the detailed textural and compositional information stored within digital rock images below the resolution of micro-CT imaging. This information may be observed in high-resolution 2D transmitted light microscopy images. Textural information impacts not only the tortuosity of the flow path, impacting permeability, but also influences how the rock will respond to stress. Compositional information could also be extracted to not only better characterize the wettability of rocks for relative permeability simulations, but also to supplement petrographic information in diagenetic modeling, among other applications. Ultimately, a full characterization of a digital rock should replicate the acoustic, geomechanical, and petrophysical properties of the imaged sample. The first step toward achieving full digital simulation of rock properties is the fundamental characterization of the sample — extracting the textural and compositional information from digital rock images. Unfortunately, this is a nontrivial undertaking. It involves acquiring sample images, segmenting pores from individual rock minerals, separating these minerals into individual grains and cements, and computing multiple attributes from the segmented grains. To address this issue, we are developing a workflow to compute key textural attributes from images with a long-term vision for the incorporation of geologic characterization into DRP using machine learning.
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Yale, David P. "Recent advances in rock physics." GEOPHYSICS 50, no. 12 (December 1985): 2480–91. http://dx.doi.org/10.1190/1.1441879.

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The need to extract more information about the subsurface from geophysical and petrophysical measurements has led to a great interest in the study of the effect of rock and fluid properties on geophysical and petrophysical measurements. Rock physics research in the last few years has been concerned with studying the effect of lithology, fluids, pore geometry, and fractures on velocity; the mechanisms of attenuation of seismic waves; the effect of anisotropy; and the electrical and dielectric properties of rocks. Understanding the interrelationships between rock properties and their expression in geophysical and petrophysical data is necessary to integrate geophysical, petrophysical, and engineering data for the enhanced exploration and characterization of petroleum reservoirs. The use of amplitude offsets, S‐wave seismic data, and full‐waveform sonic data will help in the discrimination of lithology. The effect of in situ temperatures and pressures must be taken into account, especially in fractured and unconsolidated reservoirs. Fluids have a strong effect on seismic velocities, through their compressibility, density, and chemical effects on grain and clay surfaces. S‐wave measurements should help in bright spot analysis for gas reservoirs, but theoretical considerations still show that a deep, consolidated reservoir will not have any appreciable impedance contrast due to gas. The attenuation of seismic waves has received a great deal of attention recently. The idea that Q is independent of frequency has been challenged by experimental and theoretical findings of large peaks in attenuation in the low kHz and hundreds of kHz regions. The attenuation is thought to be due to fluid‐flow mechanisms and theories suggest that there may be large attenuation due to small amounts of gas in the pore space even at seismic frequencies. Models of the effect of pores, cracks, and fractures on seismic velocity have also been studied. The thin‐crack velocity models appear to be better suited for representing fractures than pores. The anisotropy of seismic waves, especially the splitting of polarized S‐waves, may be diagnostic of sets of oriented fractures in the crust. The electrical properties of rocks are strongly dependent upon the frequency of the energy and logging is presently being done at various frequencies. The effects of frequency, fluid salinity, clays, and pore‐grain geometry on electrical properties have been studied. Models of porous media have been used extensively to study the electrical and elastic properties of rocks. There has been great interest in extracting geometrical parameters about the rock and pore space directly from microscopic observation. Other models have focused on modeling several different properties to find relationships between rock properties.
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Ball, Vaughn, J. P. Blangy, Christian Schiott, and Alvaro Chaveste. "Relative rock physics." Leading Edge 33, no. 3 (March 2014): 276–86. http://dx.doi.org/10.1190/tle33030276.1.

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Handoyo, Handoyo, Fatkhan Fatkhan, Fourier D. E. Latief, and Harnanti Y. Putri. "Estimation of Rock Physical Parameters Based on Digital Rock Physics Image, Case Study: Blok Cepu Oil Field, Central Java, Indonesia." Jurnal Geofisika 16, no. 1 (March 22, 2018): 21. http://dx.doi.org/10.36435/jgf.v16i1.53.

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Modern technique to estimate of the physical properties of rocks can be done by means of digital imagingand numerical simulation, an approach known as digital rock physics (DRP: Digital Rock Physics). Digital rockphysics modeling is useful to understand microstructural parameters of rocks (pores and rock matrks), quite quickly and in detail. In this paper a study was conducted on sandstone reservoir samples in a rock formation. The core of sandstone samples were calculated porosity, permeability, and elasticity parameters in the laboratory. Then performed digital image processing using CT-Scan that utilizes X-ray tomography. The result of digital image is processed and done by calculation of digital simulation to calculate porosity, permeability, and elastic parameter of sandstones. In addition, there are also predictions of p-wave velocity and wave -S using the empirical equations given by Han (1986), Raymer (1990), and Nur (1998). The results of digital simulation (DRP) in this study provide a higher than the calculations in the laboratory. The digital rock physicsmethod (DRP) combined with rock physics modeling can be a practical and rapid method for determining the rock properties of tiny (microscopic) rock fragments
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Avseth, Per, Tor Arne Johansen, Aiman Bakhorji, and Husam M. Mustafa. "Rock-physics modeling guided by depositional and burial history in low-to-intermediate-porosity sandstones." GEOPHYSICS 79, no. 2 (March 1, 2014): D115—D121. http://dx.doi.org/10.1190/geo2013-0226.1.

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We present a new rock-physics modeling approach to describe the elastic properties of low-to-intermediate-porosity sandstones that incorporates the depositional and burial history of the rock. The studied rocks have been exposed to complex burial and diagenetic history and show great variability in rock texture and reservoir properties. Our approach combines granular medium contact theory with inclusion-based models to build rock-physics templates that take into account the complex burial history of the rock. These models are used to describe well log data from tight gas sandstone reservoirs in Saudi Arabia, and successfully explain the pore fluid, rock porosity, and pore shape trends in these complex reservoirs.
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Dræge, Anders. "Geo-consistent depth trends: Honoring geology in siliciclastic rock-physics depth trends." Leading Edge 38, no. 5 (May 2019): 379–84. http://dx.doi.org/10.1190/tle38050379.1.

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A new method for modeling rock-physics depth trends called “geo-consistent depth trend modeling” is presented. No new rock-physics models are developed in this work, but existing models are put together in a new workflow. The workflow integrates rock-physics modeling with petrologic porosity models that account for burial, pressure, and temperature history. The new approach honors geologic trends, patterns, and cyclicity in the rocks. Examples based on well data are given to show how depositional trends can influence seismic response and depth trends. Geo-consistent depth trends are compared with the standard method for rock-physics depth trends, and differences are discussed. Geo-consistent depth trends can contribute to increased understanding of the subsurface and give input to risking of targets in exploration.
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Dissertations / Theses on the topic "Rock physics"

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Ahmed, Zubair. "Rock Physics Characterization using Physical Methods on Powders." Thesis, Curtin University, 2018. http://hdl.handle.net/20.500.11937/75690.

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This study describes a detailed investigation of quantifying key micro-structural parameters of the unconsolidated granular media and their relationship with the grain shape factors calculated from micro-CT images. These parameters are combined with the contact based effective medium models to calculate the elastic properties of the constituent grains after utilising stress dependent ultrasonic velocities of the samples. Thus developed techniques produce good results for mono-mineral quartz sands and one of the poly-mineral rock powder.
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Zhang, John Jianlin. "Time-lapse seismic surveys, rock physics basis." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp05/MQ65147.pdf.

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DIAS, JONATAN DE OLIVEIRA. "ROCK PHYSICS MODELING EVALUATION FOR CARBONATE RESERVOIRS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2017. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=36561@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO
PROGRAMA DE EXCELENCIA ACADEMICA
Desde a década de 80, abordagens data-driven têm sido utilizadas para identificação de fluidos e caracterização de reservatórios carbonáticos e siliciclásticos principalmente em relação à análise das amplitudes sísmicas. No entanto, técnicas aplicadas com sucesso para rochas siliciclásticas, como por exemplo: Análise AVO, inversões sísmicas e IDH (Indicadores Diretos de Hidrocarbonetos) revelaram não obter o mesmo êxito para reservatórios carbonáticos heterogêneos. Em contrapartida, diversos artigos mostram que fluxos de caracterização de reservatórios com modelos de física de rochas incorporados têm alcançado grande sucesso para obtenção de propriedades petrofísicas e atributos elásticos de ambas as rochas, utilizando sísmicas e well logs, em uma abordagem model-driven, focada nas características microestruturais do reservatório. Dessa forma, levando em consideração a importância de se utilizar modelos de física de rochas no escopo da caracterização de reservatórios, dois modelos de física de rochas - Xu e Payne e T-Matrix - foram aplicados, comparados e seus parâmetros foram estocasticamente avaliados e otimizados em um arcabouço Bayesiano. Através dessa abordagem, foi possível estimar, de uma forma confiável, os atributos elásticos de um reservatório carbonático (coquinas) levando em consideração diversos tipos de incertezas. Além disso, após a calibração e validação de ambos os modelos de física de rochas para diferentes poços, análises de sensibilidade foram realizadas para compreensão de forma quantitativa do comportamento dos atributos elásticos das coquinas em relação às alterações do conteúdo mineralógico, tipos de poro e fluidos desse reservatório.
Since the 80 s, data-driven approaches have been used for fluids identification and reservoir characterization of siliciclastic and carbonate rocks mainly regarding seismic amplitudes analyses. However, techniques successfully applied for siliciclastic rocks, such as: AVO analysis, seismic inversions and DHI (Direct Hydrocarbon Indicators) ranking revealed not have achieved the same outstanding and reliable results for heterogeneous carbonate rocks. On the other hand, several articles demonstrate that reservoir characterization workflows with rock physics models embedded have been reaching a robust success in order to obtain petrophysical properties and elastic attributes of both rocks, from the seismic and well logs, in a model-driven approach focused on the reservoirs microstructural information. In this way, taking into account the importance of applying rock physics models in the scope of reservoir characterization, two rock physics models - Xu and Payne and T-Matrix - were applied, compared and their parameters were stochastically evaluated and optimized in a Bayesian framework. Through this approach, it was possible to estimate, in a reliable manner, the elastic attributes of a carbonate reservoir (coquinas) taking into consideration different kinds of uncertainties. Furthermore, after the calibration in the well location and validation of both rock physics models for other wells, sensitivity analyses were conducted in order to quantitatively understand how the coquinas elastic attributes behave regarding the variations in the reservoir mineralogical content, pore shapes and fluids.
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Hoang, Phuong. "Rock physics depth trend analysis using seismic stacking velocity." Thesis, Norwegian University of Science and Technology, Department of Petroleum Engineering and Applied Geophysics, 2006. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-1631.

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Quantitative seismic interpretation is becoming more and more important in exploration and characterization of petroleum reservoirs. In this technology, rock physic analysis combined with seismic attributes has become a key strategy.

Nature creates inhomogeneous anisotropic rocks where the rock physics properties vary at different positions and directions. It is important to analyze and quantify the property changes as a function of depositional and burial trends in order to improve our detectability of petroleum reservoirs from seismic data.

In this thesis, we have presented a new methodology to obtain rock physics properties as a function of burial depth, i.e., rock physics depth trends (RPDTs), from well log and seismic data. To obtain RPDTs, several authors have suggested using rock physics models calibrated to well log data or constrained by diagenetic models. We present an alternative way to extract these from seismic stacking velocities. This is the main focus of the thesis.

We apply our methodology to extract RPDTs from seismic stacking velocities in the Njord Field area, located in the Norwegian Sea. We find that the seismic interval velocity trend matches nicely to the sonic velocity at the well location, especially above Base Cretaceous. By combining empirical RPDTs with seismic RPDTs, we are able to interpret and quantify the rock properties of different rock physics events that have occurred in Njord Field at well location and in the areas without well log information.

In this thesis we have successfully demonstrated how stacking velocities can be used to improve our understanding about normal mechanical compaction trends, tectonic activity and diagenetic events. This information is important for improved overburden and reservoir characterization, especially in areas with sparse or no well log data.

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Beloborodov, Roman. "Compaction Trends of Shales: Rock Physics and Petrophysical Properties." Thesis, Curtin University, 2017. http://hdl.handle.net/20.500.11937/68259.

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Shale is the most abundant and the least known type of sedimentary rock. It is found in every basin associated with hydrocarbon depositions and is notorious for its complicated properties. This thesis is dedicated to investigation of the compaction trends of rock physics and petrophysical properties of shale. It is supplemented with in-depth analysis of shale microstructure as a key parameter controlling the macroscopic anisotropic properties of shale.
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Rimstad, Kjartan. "Bayesian Seismic Lithology/Fluid Inversion Constrained by Rock Physics Depth Trends." Thesis, Norwegian University of Science and Technology, Department of Mathematical Sciences, 2008. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-9772.

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In this study we consider 2D seismic lithology/fluid inversion constrained by rock physics depth trends and a prior lithology/fluid Markov random field. A stochastic relation from porosity and lithology/fluid to seismic observations is established. The inversion is done in a Bayesian framework with an approximate posterior distribution. Block Gibbs samplers are used to estimate the approximate posterior distribution. Two different inversion algorithms are established, one with the support of well observations and one without. Both inversion algorithms are tested on a synthetic reservoir and the algorithm with well observations is also tested on a data set from the North Sea. The classification results with both algorithms are good. Without the support of well observations it is problematic to estimate the level of the porosity trends, however the classification results are approximately translation invariant with respect to porosity trends.

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Spikes, Kyle Thomas. "Probabilistic seismic inversion based on rock-physics models for reservoir characterization /." May be available electronically:, 2008. http://proquest.umi.com/login?COPT=REJTPTU1MTUmSU5UPTAmVkVSPTI=&clientId=12498.

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Wisman, Putri Sari. "Rock physics changes due to CO2 injection : the CO2CRC Otway Project." Thesis, Curtin University, 2012. http://hdl.handle.net/20.500.11937/737.

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The CO2CRC Otway Project aims to demonstrate that CO2 can be safely stored in a depleted gas field and that an appropriate monitoring strategy can be deployed to verify its containment. The project commenced in 2005, with the baseline 3D seismic collected early in January 2008. CO2 was injected into depleted gas reservoir known as Waarre-C at Naylor field in April 2008. The first monitor survey was recorded in January 2009, shortly after the injection of 35,000 tonnes of CO2. Early predictions in the program suggested that the resulting time-lapse seismic effect will be very subtle because of the reservoir depth, small area, complexity, small amount of CO2/CH4 in 80/20 ratio injected and most of all partial saturation of the reservoir sand. The key challenge than presented to this research was how subtle exactly is the effect going to be? To answer that question I had to develop a workflow that will produce very accurate prediction of the elastic property changes in the reservoir caused by CO2 injection. Then the sensitivity of time-lapse seismic methodology in detecting subtle changes in the reservoir is investigated.The rock physics model I propose uses the “effective” grain bulk modulus (Kgrain) to represent the average mineralogy of the grains. The validity of this approach is confirmed by good agreement achieved between Vpsat core with Vpsat computed from the log data using the “effective” modulus. . The use of “effective” Kgrain was further justified by petrographic analysis. This has increased the modelling precision and changed the predicted time-lapse effect due to CO2 injection from 3% as an average over the reservoir sequence as previously computed to nearly 6%. The significance is that 6% change could be detected with high precision monitoring methodologies. The in-situ saturation type is homogeneous, according to the analysis path assumed in this thesis. If some patchiness exists in the reservoir it will be away from the wells and it would further elevate CO2 related seismic effect.The time-lapse seismic methodology at Otway site utilised very high survey density in order to increase sensitivity. On the negative side, weak sources and the change of the source type between the surveys resulted in non-repeatability greater or of the similar order as the time-lapse signal were expected to be. Hence the interpretation of the time-lapse P-wave seismic data assumed somewhat different path. I used the model-based post-stack seismic acoustic inversion in a similar way that history matching is used in reservoir simulation studies. I performed successive fluid substitutions, followed by the well ties and inversions. The objective was to look into the inversion error. Then the modelled fluid saturation case that result in minimal inversion error reflects the most likely state of the reservoir. Modelling using 35,000 tonnes of CO2/CH4 mix with 35% water saturation and 65% CO2/CH4 mix produced the smallest error when reinstating logs to the 2009 reservoir state.The time-lapse anomaly observed in the data exceeds predictions derived through the rock physics model, seismic modelling and simulation models. This is likely to be the case in general as the effect of CO2 onto a reservoir is difficult to predict. A “conservative” approach may result in an under-prediction of time-lapse seismic effects. Consequently, the predicted and measured seismic effects can be used as the lower and the upper bound of the time-lapse effects at Naylor field, respectively. The method presented here for analysis of a subtle time-lapse signal could be applied to the cases with similar challenges elsewhere.
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Cauchefert, Matthieu. "Rock Physics Properties of Artificial Shales: Effect of Organic Matter Characteristics." Thesis, Curtin University, 2019. http://hdl.handle.net/20.500.11937/81045.

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The objective of this project is to evaluate the influence of an array of organic matter characteristics on the physical properties (elastic and dielectric) of artificial organic-rich shales. We found evidence of the impact of the following variables: thermal maturity, kerogen type, organic particles texture and deposition method. The achievements of this study are also technical. We designed an advanced compaction cell recording petrophysical and elastic properties during consolidation and an artificial thermal maturation equipment.
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Tomlinson, Simon Michael. "Computer simulation studies of rock-salt structured binary transition metal oxides." Thesis, University College London (University of London), 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.264941.

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Books on the topic "Rock physics"

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Korvin, Gabor. Statistical Rock Physics. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-46700-4.

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Singh, Kumar Hemant, and Ritesh Mohan Joshi, eds. Petro-physics and Rock Physics of Carbonate Reservoirs. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-13-1211-3.

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Ahrens, Thomas J., ed. Rock Physics & Phase Relations. Washington, D. C.: American Geophysical Union, 1995. http://dx.doi.org/10.1029/rf003.

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Vinciguerra, Sergio, and Yves Bernabé, eds. Rock Physics and Natural Hazards. Basel: Birkhäuser Basel, 2009. http://dx.doi.org/10.1007/978-3-0346-0122-1.

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Vinciguerra, Sergio. Rock physics and natural hazards. Basel, Switzerland: Birkhauser Verlag AG, 2009.

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1936-, Ahrens T. J., ed. Rock physics & phase relations: A handbook of physical constants. Washington, DC: American Geophysical Union, 1995.

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1938-, Kozák Jan, Waniek Ludvik 1930-, Československá akademie věd. Geofysikální ústav., and Symposium on Physics of Fracturing and Seismic Energy Release (1985 : Liblice Manor), eds. Physics of fracturing and seismic energy release. Basel: Birkhauser Verlag, 1987.

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Stavrogin, A. N. Experimental physics and rock mechanics: Results of laboratory studies. Lisse: A.A. Balkema, 2001.

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Liebermann, Robert C., and Carl H. Sondergeld, eds. Experimental Techniques in Mineral and Rock Physics. Basel: Birkhäuser Basel, 1994. http://dx.doi.org/10.1007/978-3-0348-5108-4.

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Morrow, C. A. High-pressure rock-physics laboratories investigate earthquake processes. [Reston, Va.]: U.S. Dept. of the Interior, U.S. Geological Survey, 2004.

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Book chapters on the topic "Rock physics"

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Korvin, Gabor. "Statistical Rock Physics." In Encyclopedia of Mathematical Geosciences, 1–17. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-26050-7_33-1.

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Korvin, Gabor. "Statistical Rock Physics." In Encyclopedia of Mathematical Geosciences, 1456–71. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-030-85040-1_33.

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Korvin, Gabor. "Entropy and Rock Physics." In Statistical Rock Physics, 265–96. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-46700-4_8.

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Korvin, Gabor. "The Internal Topology of Rocks." In Statistical Rock Physics, 83–145. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-46700-4_3.

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Korvin, Gabor. "Coordination Number of Grains." In Statistical Rock Physics, 207–27. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-46700-4_6.

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Korvin, Gabor. "Effective Properties of Rocks." In Statistical Rock Physics, 297–337. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-46700-4_9.

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Korvin, Gabor. "The Shape of Pebbles, Grains and Pores." In Statistical Rock Physics, 229–63. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-46700-4_7.

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Korvin, Gabor. "Models of Tortuosity." In Statistical Rock Physics, 51–81. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-46700-4_2.

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Korvin, Gabor. "Thermodynamic Algorithms." In Statistical Rock Physics, 381–472. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-46700-4_11.

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Korvin, Gabor. "Random Network Models." In Statistical Rock Physics, 147–77. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-46700-4_4.

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Conference papers on the topic "Rock physics"

1

Takahashi, Toru, and Soichi Tanaka. "Rock physics modeling of soft sedimentary rocks." In SEG Technical Program Expanded Abstracts 2009. Society of Exploration Geophysicists, 2009. http://dx.doi.org/10.1190/1.3255249.

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Sun, H., G. Tao, S. Vega, E. Saenger, and X. Jing. "Carbonate Rocks: A case Study to Evaluate Rock Properties Using Digital Rock Physics." In Fourth EAGE Workshop on Rock Physics. Netherlands: EAGE Publications BV, 2017. http://dx.doi.org/10.3997/2214-4609.201702450.

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Dvorkin, J., A. Tutuncu, M. Tutuncu, A. Nur, and A. Mese. "Rock Property Determination Using Digital Rock Physics." In Geophysics of the 21st Century - The Leap into the Future. European Association of Geoscientists & Engineers, 2003. http://dx.doi.org/10.3997/2214-4609-pdb.38.f054.

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Dvorkin, Jack, Joel Walls, Azra Tutuncu, Manika Prasad, Amos Nur, and Ali Mese. "Rock property determination using digital rock physics." In SEG Technical Program Expanded Abstracts 2003. Society of Exploration Geophysicists, 2003. http://dx.doi.org/10.1190/1.1817624.

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Hossain, Zakir. "Rock Physics Modeling of CO2 Bearing Reservoir Rocks." In SPE Europec/EAGE Annual Conference. Society of Petroleum Engineers, 2012. http://dx.doi.org/10.2118/154490-ms.

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Cobos, Carlos Manuel, and John P. Castagna. "Stochastic Rock Physics Inversion." In International Petroleum Technology Conference. International Petroleum Technology Conference, 2014. http://dx.doi.org/10.2523/18040-ms.

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Liu, Enru, Michael A. Payne, Shiyu Xu, Gregor Baechle, and Christopher E. Harris. "Carbonate Rock Physics Issues." In International Petroleum Technology Conference. International Petroleum Technology Conference, 2009. http://dx.doi.org/10.2523/iptc-13850-ms.

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Cobos, Carlos Manuel, and John P. Castagna. "Stochastic Rock Physics Inversion." In International Petroleum Technology Conference. International Petroleum Technology Conference, 2014. http://dx.doi.org/10.2523/iptc-18040-ms.

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"Rock Physics Complete Session." In SEG Technical Program Expanded Abstracts 2016. Society of Exploration Geophysicists, 2016. http://dx.doi.org/10.1190/segam2016-rp.

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Saenger*, Erik H., Claudio Madonna, Maria Osorno, David Uribe, and Holger Steeb. "Digital carbonate rock physics." In SEG Technical Program Expanded Abstracts 2014. Society of Exploration Geophysicists, 2014. http://dx.doi.org/10.1190/segam2014-0479.1.

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Reports on the topic "Rock physics"

1

Drury, M. Rock physics studies at the Earth Physics Branch. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1985. http://dx.doi.org/10.4095/315272.

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Dvorkin, Jack, and Gary Mavko. Rock Physics of Geologic Carbon Sequestration/Storage. Office of Scientific and Technical Information (OSTI), May 2013. http://dx.doi.org/10.2172/1097614.

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Amos Nur. Seismic-Scale Rock Physics of Methane Hydrate. Office of Scientific and Technical Information (OSTI), January 2009. http://dx.doi.org/10.2172/945215.

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McConnell, Daniel. Advanced Gas Hydrate Reservoir Modeling Using Rock Physics. Office of Scientific and Technical Information (OSTI), December 2017. http://dx.doi.org/10.2172/1435441.

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Gary Mavko. SEISMIC AND ROCK PHYSICS DIAGNOSTICS OF MULTISCALE RESERVOIR TEXTURES. Office of Scientific and Technical Information (OSTI), August 2004. http://dx.doi.org/10.2172/834112.

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Gary Mavko. SEISMIC AND ROCK PHYSICS DIAGNOSTICS OF MULTISCALE RESERVOIR TEXTURES. Office of Scientific and Technical Information (OSTI), October 2003. http://dx.doi.org/10.2172/822709.

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Gary Mavko. SEISMIC AND ROCK PHYSICS DIAGNOSTICS OF MULTISCALE RESERVOIR TEXTURES. Office of Scientific and Technical Information (OSTI), June 2003. http://dx.doi.org/10.2172/822710.

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Gary Mavko. SEISMIC AND ROCK PHYSICS DIAGNOSTICS OF MULTISCALE RESERVOIR TEXTURES. Office of Scientific and Technical Information (OSTI), May 2002. http://dx.doi.org/10.2172/822711.

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Gary Mavko. SEISMIC AND ROCK PHYSICS DIAGNOSTICS OF MULTISCALE RESERVOIR TEXTURES. Office of Scientific and Technical Information (OSTI), June 2003. http://dx.doi.org/10.2172/822712.

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Gary Mavko. SEISMIC AND ROCK PHYSICS DIAGNOSTICS OF MULTISCALE RESERVOIR TEXTURES. Office of Scientific and Technical Information (OSTI), June 2003. http://dx.doi.org/10.2172/822713.

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