Reservoir Imaging Research Articles

The Identification and Quantification of Hidden Hazards in Small Scale Reservoir Engineering Based on Deep Learning: Intelligent Perception for Safety of Small Reservoir Projects in Jiangxi Province

This study aims to enhance the detection and assessment of safety hazards in small-scale reservoir engineering using advanced image processing and deep learning techniques. Given the critical importance of small reservoirs in flood management, water supply, and ecological balance, the effective monitoring of their structural integrity is crucial. This paper developed a fully convolutional semantic segmentation method for hidden danger images of small reservoirs using an encoding–decoding structure, utilizing a deep learning framework of convolutional neural networks (CNNs) to process and analyze high-resolution images captured by unmanned aerial vehicles (UAVs). The method incorporated data augmentation and adaptive learning techniques to improve model accuracy under diverse environmental conditions. Finally, the quantification data of hidden dangers (length, width, area, etc.) were obtained by converting the image pixels to the actual size. Results demonstrate significant improvements in detecting structural deficiencies, such as cracks and seepage areas, with increased precision and recall rates compared to conventional methods, and the HHSN-25 network (Hidden Hazard Segmentation Network with 25 layers) proposed in this paper outperforms other methods. The main evaluation indicator, mIoU of HHSN-25, is higher than other methods, reaching 87.00%, and the Unet is 85.50%, and the Unet++ is 85.55%. The proposed model achieves reliable real-time performance, allowing for early warning and effective management of potential risks. This study contributes to the development of more efficient monitoring systems for small-scale reservoirs, enhancing their safety and operational sustainability.

Research on spatial carving method of glutenite reservoir based on opacity voxel imaging

The glutenite reservoir in an exploration area in eastern China is well-developed and holds significant exploration potential as an important oil and gas alternative layer. However, due to the influence of sedimentary characteristics, the glutenite reservoir exhibits strong lateral heterogeneity, significant vertical thickness variations, and low accuracy in reservoir space characterization, which affects the reasonable and effective deployment of development wells. Seismic data contains the three-dimensional spatial characteristics of geological bodies, but how to design a suitable transfer function to extract the nonlinear relationship between seismic data and reservoirs is crucial. At present, the transfer functions are concentrated in low-dimensional or high-dimensional fixed mathematical models, which cannot accurately describe the nonlinear relationship between seismic data and complex reservoirs, resulting in low spatial description accuracy of complex reservoirs. In this regard, this paper first utilizes a fusion method based on probability kernel to fuse seismic attributes such as wave impedance, effective bandwidth, and composite envelope difference. This provide a more intuitive reflection of the distribution characteristics of glutenite reservoirs. Moreover, a hybrid nonlinear transfer function is established to transform the fused attribute cube into an opaque attribute cube. Finally, the illumination model and ray casting method are used to perform voxel imaging of the glutenite reservoirs, brighten the detailed characteristics of reservoir space, and then form a set of methods for ' brightening reservoirs and darkening non-reservoirs ', which improves the spatial engraving accuracy of glutenite reservoirs.

Forecasting the Coastal Systems State using Mathematical Modelling Based on Satellite Images

Introduction. Coastal systems of Southern Russia are constantly exposed to biotic, abiotic and anthropogenic factors. In this regard, there is a need to develop non-stationary spatially inhomogeneous interconnected mathematical models that make it possible to reproduce various scenarios for the dynamics of biological and geochemical processes in coastal systems. There is also the problem of the practical use of mathematical modelling, namely its equipping with real input data (boundary, initial conditions, information about source functions). An operational source of field information can be data received from artificial Earth satellites. Therefore, the problem arises of identifying phytoplankton populations in images of reservoirs, which, as a rule, have a spotty structure, with low image contrast relative to the background, as well as determining the boundaries of their location.Materials and Methods. This work is based on the correct application of modern mathematical analysis methods, mathematical physics and functional analysis, the theory of difference schemes, as well as methods for solving grid equations. Biogeochemical processes are described based on convection-diffusion-reaction equations. Linearization of the constructed model is carried out on a time grid with step τ. A method for recognizing the boundaries of spotted structures is being developed based on Earth remote sensing data. A combination of methods is considered as image processing algorithms: local binary patterns (LBP) and a two-layer neural network.Results. The developed software-algorithmic tools for space image recognition are presented, based on a combination of methods — local binary patterns (LBP) and neural network technologies, focused on the subsequent input of the obtained initial conditions for the problem of phytoplankton dynamics into a mathematical model. Regarding the necessary mathematical model, a continuous linearized model has been proposed and studied, and on its basis a linearized discrete model of biogeochemical cycles in coastal systems, for which practically acceptable time step values have been established for numerical (predictive) modelling of problems of the dynamics of planktonic populations and biogeochemical cycles, including in the event of death phenomena, which makes it possible to reduce the time of operational forecasting. At the same time, for the constructed discrete model, properties that are practically significant for discrete models are guaranteed to be satisfied: stability, monotonicity and convergence of the difference scheme, which is important for reliable forecasts of adverse and dangerous phenomena.In the process of work, referring to satellite images, which make it possible to obtain the state of coastal systems with high accuracy, initial conditions are entered into the mathematical (computer) model. The model analyzes satellite image data and determines levels of “pollution”, the formation of extinction zones and other factors that may threaten nature.Discussion and Conclusion. Discussion and conclusions. Using this model, it is possible to predict possible changes in coastal ecosystems and develop strategies to protect them. The results obtained make it possible to significantly reduce the time of forecast calculations (by 20−30 %) and increase the likelihood of early detection of unfavorable and dangerous phenomena, such as intense “blooming” of the aquatic environment and the formation of extinction zones in coastal systems.

Simulation and analysis of elastic waves in partially saturated double-porosity media based on finite difference method

Double-porosity poroelastic model takes into account the effect of mesoscopic flow induced by rock heterogeneity on dispersion and attenuation of elastic waves, and has obtained good application results in the quantitative explanation of seismic data in heterogeneous reservoirs. Wavefield simulation based on double-porosity model not only helps visualize the propagation characteristics of the elastic waves but also lays the foundation for seismic imaging. In this work, we perform wavefield simulation and analysis based on the Santos-Rayleigh model which incorporates mesoscopic and global flow in a partially-saturated double-porosity medium. Specifically, the mesoscopic flow mechanism is represented with a Zener viscoelastic model. The comparison shows that the Zener model can accurately capture the propagation characteristics of fast P-wave, but fails to describe the attenuation characteristics of slow P3 wave in the low-frequency band. It implies that Zener viscoelastic model and slow wave modes follow different mechanisms. Then the staggered grid finite-difference method is used to simulate wave propagation in a double-porosity medium, and the stiff problem is solved with a time-splitting algorithm, which can significantly improve computational efficiency. Based on the above methods, the correctness of our algorithm is verified with derived analytical solution for a P-wave source in a uniform partially saturated poroelastic medium. Analytical and numerical solutions are in good agreement and mean error is 0.33%. We provide some examples of wavefield snapshots and seismograms in homogeneous and layered heterogeneous media at seismic and ultrasonic frequencies. The simulation results demonstrate the strong attenuation of fast P-wave and no change of S-wave in the seismic band due to mesoscopic flow mechanism, which is consistent with the theoretical prediction of double-porosity model. Moreover, the energy of fast P-wave is concentrated in solid phase while slow waves are stronger in fluid phase. This work contributes to the understanding of broadband elastic wave propagation in a heterogeneous partially saturated porous medium and can be applied to the reservoir imaging with broadband geophysical data.

Wide azimuth seismic data processing technology and application: a case study of tight gas reservoirs in western China

As the difficulty of oil and gas field exploration and development increases both domestically and internationally, onshore exploration targets have gradually shifted from the shallow to the deep and from conventional oil and gas reservoirs to unconventional ones. Particularly in the exploration and development of unconventional oil and gas horizontal wells, there is an increasing demand for higher precision and quality of seismic data to better identify formation lithology, rock fractures, and improve the characterization of reservoirs, reservoir positioning, and connectivity. Wide-azimuth seismic exploration possesses significant technical advantages in addressing exploration challenges such as lithologic exploration, small fault imaging, and detailed characterization of oil and gas reservoirs. Wide azimuth seismic data reduces blind spots in seismic acquisition and improves the imaging accuracy of small faults. Notably, there exist distinct anisotropic characteristics in fault areas and fractured reservoirs. Wide azimuth seismic data is particularly advantageous for studying amplitude variation with variations in amplitude with offset (AVO), incident angle (AVA), or azimuth (AVAZ), as well as velocity with azimuth (VVA). These variations aid in identifying faults, fractures, and changes in formation lithology. As the focus of oil and gas exploration gradually shifts to complex lithological reservoirs and unconventional oil and gas reservoirs, narrow azimuth seismic exploration has been gradually replaced by wide azimuth exploration. However, as observation azimuth increases, challenges related to velocity variations with azimuth, azimuth-related traveltime differences, and azimuth-related anisotropy arise. Based on wide-azimuth seismic data from tight gas reservoirs in western China, this study conducted wide-azimuth anisotropic velocity analysis, OVT domain data regularization processing, OVT domain prestack time/depth migration, and horizontally transverse isotropy (HTI) azimuth anisotropy correction techniques. After applying specialized processing to the wide-azimuth seismic data, significant improvements were observed in the S/N and resolution of the target layer. The delineation of fractures related to hydrocarbon sources also became more distinct. These advancements not only provided high-quality results for high-fidelity, high-resolution imaging of tight gas reservoirs but also provided azimuth volume corresponding to fast and slow wave velocities for seismic data interpretation, facilitating velocity variation with azimuth (VVAZ) fracture detection and AVO analysis research.

Atlantis — 20 years of seismic innovation finally removes the shroud of mystery

The Atlantis Field has gone through more than two decades of continuous seismic imaging efforts, during which time many innovative technologies were incubated, the most recent one being the successful application of full-waveform inversion (FWI) in salt environments. This technique led to a significant improvement in the subsalt image. However, imaging challenges remain for the Atlantis reservoirs, primarily due to the complex overburden salt geometries and the highly compartmentalized reservoir. Even with an improved velocity model from FWI, the conventional reverse time migration (RTM) images still suffer from illumination issues and contain strong migration swings that hinder the subsalt imaging and subsequent interpretations. Furthermore, early versions of FWI employed an acoustic assumption, leading to visible salt halos at the salt boundaries in the velocity model, which adversely impacted the reservoir imaging. In the last 12 months, elastic time-lag FWI (TLFWI) and FWI-derived reflectivity (FDR) imaging using long-offset ocean-bottom node data have minimized these imaging issues at Atlantis, providing another step change in subsalt understanding. Although the 3D RTM images using the elastic FWI velocity model are similar overall to their acoustic counterparts, the 4D time-lapse RTM images at Atlantis show noticeable improvements. Furthermore, FDR images derived from elastic FWI velocities show obvious benefits over the acoustic ones. With a more accurate modeling engine that allows for better match between synthetic and real data, FDR imaging shows improved illumination, higher signal-to-noise ratio, and better reservoir details over acoustic FDR imaging. This recent advancement in using elastic TLFWI has had immediate positive effects in facilitating the Atlantis Field's current and future development.

Rapid play evaluation through AI interpretation

Recent years have brought an explosion in the application of advanced AI techniques to the imaging and interpretation of petroleum reservoirs. The ability of these techniques to image features in unprecedented detail, and within very short timeframes, has provided the opportunity for the industry to gain a more complete understanding of hydrocarbon reservoirs than ever before. The rapid evolution of these technologies has brought challenges however, as new workflows must be developed to gain the greatest value from these advancements. In this paper we look at the impact of these technologies on imaging, interpretation and modelling. This is done through an analysis of datasets spanning compressional and extensional systems, looking at both onshore and offshore data. A particular focus is given to recent acreage release areas. Through this analysis we find significant opportunities to revolutionise G&G workflows, but also unexpected challenges in understanding and integrating this newfound complexity. The given examples show that the interpreter is no longer working with the artificial simplicity of manually interpreted structures, but rather with a web of localised planes of slippage. Rather than the challenge of accurately identifying faults, we must focus on how to transfer this complexity into a useful interpretation and then into our static model. In these examples we can see that, through a reduction in manual processes, the interpreter can focus more of their energy on the iterative process of proposing and refining structural models, and that this process proves crucial to working effectively with these new methods.

3-D body-wave tomography from the seismic ambient noise recorded by a dense array in the Dehdasht area, Iran

SUMMARY The strong attenuation of the thick sedimentary layers in the Dehdasht region, Iran, renders active seismic exploration surveys difficult. The imaging of the existent limestone reservoirs is limited to the shallow subsurface due to the strong attenuation of seismic waves. Here, we discuss a different approach to imaging the subsurface using body waves extracted from the cross-correlation of the seismic ambient wavefield. We discuss the technical challenges to extracting clear P-wave arrivals from the seismic ambient wavefield of a dense 3-component seismic array deployed in the Dehdasht basin. We invert the data for the 3-D P-wave velocity structure and compare the velocity model with results from the 2-D active seismic surveys in the area. The results show the potential of using body waves extracted from the seismic ambient wavefield for imaging purposes in highly attenuating areas.

Processes and timescales of magmatic rejuvenation and residence prior to post-caldera rhyolitic eruptions: Ōkataina Volcanic Centre, Aotearoa New Zealand

Understanding the timescales and processes through which magma bodies form and develop in the crust prior to eruption is vital for volcanic monitoring and interpreting future unrest signals, particularly at caldera volcanoes. Here we present the results of a case study on Ōkataina Volcanic Centre, New Zealand, into the timescales of pre-eruptive processes operating during young intra-caldera eruptions, using Fe-Mg interdiffusion profiles in orthopyroxene. Three eruptions covering the three different vent regions, the 15.6 ka Rotorua episode from the Ōkareka Embayment, the 14.0 ka Waiohau episode from Tarawera, and the 5.5 ka Whakatāne episode from Haroharo have broadly similar rhyolitic compositions but show distinctions in their mineralogy and crystal zoning profiles. Back-scattered electron imaging coupled with major-element analyses of orthopyroxene cores and rims imply that open-system mixing and disequilibrium is a common process in the early stages of magma assembly at Ōkataina. Through interpreting mineral chemistry and zoning patterns, we infer that melt segregation, magma body assembly from the source mush and residence in the upper crust takes place on the order of decades up to several centuries, or (if prematurely triggered) as short as months. Priming events such as heating by basaltic injection (common in the Ōkataina rhyolite eruptions) occur over decades prior to eruption. Our findings highlight that multiple processes can dictate the assembly, residence and eruption of melt bodies from the crust and that most magmatic processes occur over timescales that are short enough to be directly relevant to geophysical imaging of magma reservoirs and monitoring initiatives.

Petrographic recognition and classification of bioclastic carbonate thin sections based on attention mechanism

The huge reserves of carbonate reservoirs have become an important target for oil and gas exploration and development, but their complex pore structure makes petrographic identification difficult, while the traditional identification and classification process using manual analysis of rock thin sections suffers from problems such as being susceptible to subjective factors and being time-consuming. To address these problems, this paper proposes a new method for the intelligent classification of thin sections based on an attention mechanism. Firstly, 295 original images of carbonate reservoirs in the Haffaya oil field of Iraq in the Middle East are used for training to obtain a network model that can directly use rock thin sections images as input variables for analysis of the classification network. It was then classified into seven categories according to Dunham's classification method and compared with the ResNet classification network. The results show that the combined accuracy of the method is 13.8% higher than that of the ResNet network, reaching 93.6%; it can effectively extract the relevant characteristics of rock thin sections under the condition of small sample data, and has strong applicability in complex carbonate reservoirs.

A Study on the Acquisition Technology for Weak Seismic Signals from Deep Geothermal Reservoirs

There are rich geothermal resources in China and they are widely distributed. After years of continuous exploration and production, most of the shallow geothermal resources have been explored and the current exploration mainly focuses on deep ones. Among a great many geophysical exploration methods, seismic survey is the most effective means of geothermal resource exploration and production, but its weak seismic reflection signal, low S/N ratio and poor imaging of thermal reservoirs due to the seismic geological conditions restrict the production and utilization of deep geothermal resources. It considers through the analysis of the geophysical characteristics of the thermal reservoir that the main causes for the weak seismic reflection signals from deep thermal reservoirs are (1) the shielding effect of the strong wave impedance interface between the thermal reservoir and the caprocks; (2) the small reflection coefficient inside the thermal reservoir; and (3) the serious absorption and attenuation of high-temperature fluids such as hydrothermal fluids and steam in the thermal reservoirs by seismic waves. Accordingly, a series of seismic data acquisition technologies are proposed based on the high-precision vibroseis low-frequency shooting, high-sensitivity geophones long-spread receiving and small bin size highfold technologies, and their application in the seismic acquisition of dry-hot rocks (HDR) in Gonghe Basin, Qinghai, shows a very good application effect.

Using Dark Fiber and Distributed Acoustic Sensing to Characterize a Geothermal System in the Imperial Valley, Southern California

AbstractThe Imperial Valley, CA, is a tectonically active transtensional basin located south of the Salton Sea; the area hosts numerous geothermal fields, including significant hidden hydrothermal resources without surface manifestations. Development of inexpensive, rugged, and highly sensitive exploration techniques for undiscovered geothermal systems is critical for accelerating geothermal power deployment as well as unlocking a low‐carbon energy future. We present a case study utilizing distributed acoustic sensing (DAS) and ambient noise interferometry for geothermal reservoir imaging, utilizing unlit fiber‐optic telecommunication infrastructure (dark fiber). The study exploits two days of passive DAS data acquired in early November 2020 over a ∼28‐km section of fiber from Calipatria, CA to Imperial, CA. We apply ambient noise interferometry to retrieve coherent signals from DAS records and develop a bin stacking technique to attenuate the effects from persistent localized noise sources and to enhance retrieval of coherent surface waves. As a result, we are able to obtain high‐resolution two‐dimensional (2D) S wave velocity (Vs) structure to 3 km depth, based on joint inversion of both the fundamental and higher overtones. We observe a previously unmapped high Vs and low Vp/Vs ratio feature beneath the Brawley geothermal system, which we interpret to be a zone of hydrothermal mineralization and lower porosity. This interpretation is consistent with a host of other measurements including surface heat flow, gravity anomalies, and available borehole wireline data. These results demonstrate the potential utility of DAS deployed on dark fiber for geothermal system exploration and characterization in the appropriate geological settings.

Salt geometry in the Central Basin of the Nova Scotia passive margin, offshore Canada based on new seismic data

This study describes the structural architecture of the central portion of the Scotian Basin and focusses on Mesozoic salt deposition and deformation linked to magma-rich rifting. BP acquired a high-quality 3D seismic survey called the Tangier survey and built a detailed velocity model with RFWI (Reflection Full Waveform Inversion) and tomography. This has allowed for high resolution seismic imaging of target sedimentary reservoirs but also for the first time, imaging of the complex crustal architecture along the central part of the Nova Scotia margin. We evaluated the regional basin architecture and salt tectonic evolution in context of Late Triassic and Early Jurassic rifting followed by passive margin gravity spreading. An exploration well (Aspy D-11) was drilled based on the 3D seismic interpretation and penetrated halite, carnallite and anhydrite salt in an allochthonous salt sheet. Basement is thought to have rifted during deposition of interlayered halite, shale, carnallite and anhydrite. Carnallite may have precipitated from enriched brines that formed at the more distal (southern) end of an elongated seaway of rifted basins which began opening first in the North in the Late Triassic and propagated southward towards Florida (e.g., Jansa, 1980; Jansa and Tucholke, 1986; Roberts and Bally, 2012). Water flowed southwards from Tethys along a chain of complexly interconnected areas of rifted basins. Flow of seawater along Nova Scotia is interpreted to have been southward along a widening and progressively subsiding region of rifts possibly as dynamic elevation associated with the CAMP (Central Atlantic Magmatic Province) dissipated southward much like what occurred in the Central South Atlantic and Gulf of Mexico (GoM) (e.g., Quirk et al., 2013; Morgan et al., 2020; Pindell et al., 2020; Pindell and Heyn, 2022). Brine was enriched along the seaway by evaporation, causing deposition of the most-soluble salt components furthest south along the sequence of basins. The presence of weathered basalt in salt and SDRs on the seismic supports magma-rich Mesozoic rifting and suggests that heating of brine pools may not have been exclusively caused by the sun, but that hydrothermal systems probably contributed to heating and the precipitation of Carnallite.

PP 7.11 – 00091 In vivo and in vitro imaging of viral reservoirs to understand bystander damage during chronic HIV infection

PP 7.11 – 00091 In vivo and in vitro imaging of viral reservoirs to understand bystander damage during chronic HIV infection

Petrologic imaging of the magma reservoirs that feed large silicic eruptions

Large silicic explosive eruptions are one of Nature's most hazardous phenomena. Very few have been witnessed and unravelling the complex conditions that lead to these eruptions remains a difficult task because the characteristics of the feeding magma reservoirs are still insufficiently constrained from geophysical imaging. Here we show that a barometer based on the composition of amphibole in equilibrium with plagioclase and biotite, common minerals in the eruptive products of large silicic eruptions, records the thickness and depth of magma reservoirs with uncertainties of 0.8 and 2.7 km, respectively. Pressures are given by the equation: P (MPa) = 892 · VI Al + 101, where VI Al is the octahedral aluminum content of the amphibole. With the example of a Miocene Turkish ignimbrite, we show that reservoirs feeding large silicic eruptions can be pancake-shaped. Our new barometer, valid between 650 and 950 °C, can be used in combination with volcanological and geophysical data to infer the size, shape and depth of magma reservoirs and may serve as a tool for monitoring future activity. This temperature-independent barometer is also applicable to any volcanic or plutonic rock containing amphibole + plagioclase + biotite and is in excellent agreement with previously published temperature-dependent barometers within their calibration range. • Developpement of a new temperature-independent Al-in amphibole geobarometer • Depth of emplacement of plutons and magma reservoirs with an uncertainty of 2.7 km • Shape of erupted magma reservoirs accessible from petrological and volcanological observations

Lithology identification in carbonate thin section images of the Brazilian pre-salt reservoirs by the computational vision and deep learning

Lithology identification in carbonate thin section images of the Brazilian pre-salt reservoirs by the computational vision and deep learning

3D Demultiple Techniques Dramatically Improve the Imaging of a Giant Kashagan Reservoir in the Ultra-Shallow North Caspian Sea

Disclaimer Text and Data Mining. Any automated analytical technique aimed at analysing text and data in digital form in order to generate information including - but not limited to - patterns, trends and correlations (so-called Text and Data Mining) may only be applied if it is done by a research organisation or cultural heritage institution solely for the purpose of (non-commercial) scientific research as mentioned in Clause 3 of Directive (EU) 2019/790 (the Digital Single Market Directive) and Clause 15n of the Dutch Copyright Act [Auteurswet]. Text and Data Mining for commercial purposes is not allowed; all rights in this respect are reserved pursuant to Clause 4 paragraph 3 of the Digital Single Market Directive and Clause 15o paragraph 1 of the Dutch Copyright Act.

3D deep geothermal reservoir imaging with wireline distributed acoustic sensing in two boreholes

Abstract. Geothermal exploration will help move towards a low-carbon economy and provide a basis for green and sustainable growth. The development of new practical, reliable methods for geophysical characterization of a reservoir has the potential to facilitate a broader application of deep geothermal energy. At the Groß Schönebeck in situ laboratory, a unique vertical seismic profiling (VSP) dataset was recorded in two 4.3 km deep geothermal boreholes using fibre-optic cables in early 2017. The experiment set-up consisted of 61 vibrator points organized in a spiral pattern around the well site to ensure a proper offset and azimuth distribution in the target reservoir section. Data were processed using a standard workflow for VSP. As a result, a detailed three-dimensional 0.75km×1km×4.5 km image around the existing boreholes was created using the Kirchhoff migration algorithm with restricted aperture. The imaging resolved small-scale features in the reservoir essential for the future exploration of the geothermal research site. Borehole data with vertical resolution up to 16 m revealed the existing depth variations of the Elbe reservoir sandstone horizon at 4.08–4.10 km depth and indications of an unconformity in the area where we expect volcanic rocks. In addition, in the borehole data a complex interlaying with numerous pinch-outs in the Upper Rotliegend reservoir section (3.8 to 4 km depth) was discovered. Thereby, we demonstrate that wireline fibre-optic data can significantly contribute to exploration by providing an efficient and reliable method for deep geothermal reservoir imaging.

Pore characterization of unconventional reservoirs

This study proposes an image-based idea for analyzing the complex geometric characteristics of reservoir spaces using various change curves of the pore geometric attributes to subdivide and evaluate tight reservoir rocks from micron to centimeter thicknesses. Using advanced imaging and image-processing technologies, in this study, we transform information from reservoir images into a vertical stratigraphy via an imaging-based method. The new parameter system incorporates three categories of parameters, size (S), morphology (M), and direction (D), to quantitatively and comprehensively characterize the pores of unconventional reservoir rocks. Given these three categories of the parameters, the curve at a certain depth value can be used to clearly identify obvious interfaces, which constitute high tip values. These interfaces may indicate that the hydrodynamic conditions, stress conditions of the reservoir, temperature and pressure, or other physical or chemical conditions changed significantly at these points, allowing the sedimentary compaction process to be well documented at the microscale level. This indicates that, from a micro-level perspective, we can find micro-evidence of the hydrodynamic conditions at the time of formation. Such information can help strengthen our understanding of the geological formation processes of unconventional hydrocarbon reservoirs.

Magnetotelluric imaging of the shallow-seated magma reservoir beneath the Karadağ stratovolcano, Central Anatolia, Turkey

The central Anatolian Volcanic Province encompasses many volcanoes elongated in a northeast-southwest direction. Karadağ is one of the dormant Quaternary stratovolcanoes of the region at the southern end of the province. We acquired broadband magnetotelluric (MT) data in the period range 0.0001–251 s at 124 locations to obtain a three-dimensional electrical resistivity model to identify the associated magmatic-hydrothermal system beneath the Karadağ stratovolcano. The resistivity model provides evidence for low resistivity anomalies that include (1) a near-surface localised low resistivity (~ 20 Ωm) zone situated directly beneath the crater centre that is interpreted to be lacustrine sediments of an extinct crater lake, (2) a shallow low resistivity (~ 10 Ωm) zone of probable hydrothermal alteration in the eastern part of the stratovolcano and (3) a deep and large zone of low resistivity (<10 Ωm) attributed to a shallow-seated magma reservoir at a depth of 3 to 7 km beneath the volcanic edifice. A few hundred meters thick resistive surface layer corresponds to the Karadağ adakitic volcanics (i.e., andesites and dacites), and a resistive basement representing Precambrian to Mesozoic high- and medium-grade metamorphic rocks on the flanks is observed in the resistivity model.