Seismic Identification Research Articles

Geological characteristics and seismic identification of reservoirs in the Colorado Basin off the Atlantic coast of Argentina

Abstract The Colorado Basin is a hot exploration frontier basin conjugated with the southwest coast of Africa which has undergone four evolutionary stages: Carboniferous-Jurassic pre-rift, Jurassic-Early Cretaceous rift, Late Cretaceous transition and passive marginal drift since Paleocene. Major oil and gas discoveries have been made in the conjugated Orange Basin in recent years, including the Graff field and Venus field discovered in 2022 with recoverable reserves of 550 Mboe and 2.3 Bboe, respectively. This indicates that the basin has good oil and gas exploration potential. Based on the analysis of drilling data and seismic data, it is concluded that the basin has a mature oil-gas generation system and better reservoir conditions. The pre-rift and syn-rift source rocks are confirmed by 5 Wells with oil and gas shows in the shallow water shelf, and all have entered the hydrocarbon generation threshold. Reservoir distribution and trap-sealing conditions have become key factors in oil and gas exploration. this paper describes the reservoir characteristics in the drilling data, and extrapolates the seismic reflection characteristics of the same strata, and predicts the reservoir distribution in the unexplored area of the basin. The reservoir lithology and sedimentary facies are analyzed based on the gamma logging curves. Reservoir identification and reasonable prediction on seismic profile are mainly determined by seismic reflection amplitude and horizon calibration. The basin has three sets of reservoirs, namely, pre-rift Permian underwater fan sandstone, Lower Cretaceous alluvial fan sandstone of syn-rift period and Upper Cretaceous Colorado Formation shallow marine sandstone of transitional period. Among them, Colorado Formation sandstone reservoir has the best physical property conditions, with a maximum porosity of 32% and a thickness of 1000m. The Cretaceous and Paleogene turbidite sandstone of slope fan facies are potential reservoir in the deep waters, which mainly form litho-stratigraphic traps in the continental slope.

Seismic Identification and Characterization of Deep Strike-Slip Faults in the Tarim Craton Basin

Seismic Identification and Characterization of Deep Strike-Slip Faults in the Tarim Craton Basin

Seismic identification and characterization of complex storage space oil and gas reservoirs

Seismic identification and characterization of complex storage space oil and gas reservoirs

Quantitative Elimination of Seismic Pseudofaults and Fine Analysis of True Faults Underlying Igneous Rocks of No-Well Areas: A Case Study of Shuntuoguole Uplift in Tarim Basin

Abstract After multistage tectonic movement and evolution, large superimposed oil and gas basins generally developed many igneous rocks in the early rifting stages. The lithology and lithofacies of igneous rocks are complex, which is easy to lead to the distortion of the underlying migration velocity field and thus the response of seismic pseudofaults. Also, because of the obvious shielding and absorption effect of igneous rocks on seismic waves, the waveform quality of underlying strata is poor and the seismic response characteristics of faults are fuzzy. Currently, relevant studies have shown that the influence of igneous rock can be eliminated by the prestack depth migration with an accurate igneous rock velocity model. However, improving the accuracy of the velocity model needs to be corrected by well-logging data, resulting in poor applicability of the existing velocity modeling technology underlying igneous rocks without well, which is an obvious technical bottleneck. In this paper, the secondary strike-slip fault in Shuntuoguole low uplift of Tarim Basin, which has great oil and gas exploration potential but a very low degree of drilling, is selected as the research object. Aiming at difficult fault detection underlying igneous rocks caused by lack of drilling, the accuracy of fault seismic identification is improved by “interpretative fault preprocessing” and “fault sensitive attribute optimization.” In addition, through the “extreme hypothesis method” to maximize the complex migration velocity and simulate the underlying target layer distortion maximization, we realize the quantitative elimination of seismic pseudofaults. The practical application shows that this technology can determine the true and fake underlying faults quantitatively without establishing an accurate igneous rock velocity model. It is crucial not only for exploring oil and gas in the Tarim Basin’s secondary strike-slip faults but also for offering a method and technical guide for identifying faults in other basins affected by igneous rocks.

Seismic Identification and Hydrocarbon Accumulation Characteristics of Submarine Fan in offshore Suriname

In recent years, oil and gas fields have been continuously discovered in the Suriname-Guyana Basin of South Atlantic, the reservoir of which is submarine turbidite sandstone and become one of the hot exploration objectives in the world. Based on the interpretation and analysis of 2D seismic and well data, this paper presents the integrated geological and geophysical evaluation of the Suriname-Guyana basin within Suriname and describes the identification characteristics and hydrocarbon accumulation process of submarine fan in offshore Suriname. The tectonic evolution of this region can be divided into four stages, breakup of Pangea, intracontinental rift, regional uplift and drifting over the South Atlantic. The Upper Cretaceous marks the transition of a transgressive to a regressive system with increasing sediment input from the south west, creating a broad delta plain environment across the shallow offshore area. It has been confirmed that multi-stage submarine fans have developed from Upper Cretaceous to Neogene in offshore Suriname, with overlapping characteristics of multiple erosive surfaces. It is suggested that erosive surface forming local unconformity is the important identification mark of submarine fan. Among them, the Paleogene and Upper Cretaceous submarine fans are the most widely distributed and have the most obvious characteristics on seismic profiles. The bottom of the Paleogene and Upper Cretaceous fans are identified by the erosive surfaces. The fan root has obvious characteristics of cutting valley, forming inter-bedded with the deep-sea facies toward the outer fan, along with litho-logic granularity thinning and scope expansion. The distal parts of the submarine fan are surrounded by abyssal shale, which can form a good source, reservoir and cap configuration. Therefore, turbidite fan sandstone with good source rock and cap configuration is the favorable reservoir.

Moment tensor event identification for collapses

SUMMARY We introduce a seismic identification method for collapse events using moment tensors (MTs). We start by computing full (six-element) MT solutions for 43 identified collapse events from around the world, and statistically characterizing the population on the MT hypersphere. We then test a large data set of over 1000 full MTs for the western U.S. against the distribution of collapses using a MT-based identification method similarly as used for testing explosions. Known collapses and explosions are readily identified, along with other anomalous events in the Geysers and central California coast. Misidentification rates are determined for various screening angles with optimal misidentification rates between earthquakes and collapses on the order of 3 per cent. The method is demonstrated to be very effective at identifying non-earthquake sources with a 97–98 per cent accuracy. It is likely to be transportable to other regions, and can be used for event identification anywhere full MT solutions are routinely calculated.

Seismic identification of carbonate reservoir sweet spots using unsupervised machine learning: A case study from Brazil deep water Aptian pre-salt data

The pre-salt high-yield carbonate reservoirs of Brazil are responsible for about 75% of national oil production. Still, seventeen years since its discovery, detailed seismic characterization of these reservoirs remains challenging, with producing and nonproducing lithologies often exhibiting the same amplitude response. Those reservoirs are complex, composed of high productivity lacustrine carbonates (stromatolites and grainstones), mixed with non-producing mudstones, clays, and igneous intrusions. To address this heterogeneity, we evaluate unsupervised machine learning clustering techniques including Self Organizing Maps (SOM), Generative Topographic Maps (GTM), and K-means and apply them to a suite of instantaneous, geometric, interval velocity, and AVO seismic attributes. We use both static and dynamic reservoir data from 13 wells at the Mero field that penetrated lacustrine carbonates from Barra Velha formation to validate the accuracy of our unsupervised learning models. These wells are excellent blind tests as they were not used for any algorithm training. In this pioneer work, the first done using machine learning in the Mero field, we find that SOM, GTM, and K-means models provide clusters that can be linked to sweet spots associated with fracturing, karstification, and hydrothermal alteration. Additionally, clusters related to sill intrusions, platform facies and distal fine grained non-reservoirs were identified. The results can be extrapolated to the adjacent Central Libra Area (still in exploration phase), where we have identified the same clusters of the sweet spots reservoirs in Mero Field and, thus, they can be considered as future targets. For accuracy assessment, the same attribute combination SOM clustering was performed in another Petrobras’ pre-salt confidential dataset and the results were satisfactory. So, for exploration projects optimization purposes, the new proposed workflows can also be applied to other areas with geological similarity to the Mero Field.

Prediction of coalbed methane content based on seismic identification of key geological parameters: a case in a study area, Southern Qinshui Basin

Prediction of coalbed methane content based on seismic identification of key geological parameters: a case in a study area, Southern Qinshui Basin

Automatic Evaluation of an Interwell-Connected Pattern for Fractured-Vuggy Reservoirs Based on Static and Dynamic Analysis

The types of fractured-vuggy reservoirs are diverse, with dissolution holes and fractures of different scales as the main reservoir spaces. Clarifying the connectivity between wells is crucial for improving the recovery rate of fractured-vuggy reservoirs and avoiding problems of poor water- flooding balance and serious water channeling. A traditional dynamic connected model hardly describes the geological characteristics of multiple media, such as karst caves and fractures, which cause multiple solutions from the calculation. The static analysis is the basis for connectivity evaluation. In this study, we designed an intelligent search strategy based on an improved A* algorithm to automatically find a large-scale fractured-vuggy connected path by seismic multi-attribute analysis. The algorithm automatically evaluates the interwell-connected mode and clarifies the relationship between the static connected channel and the fractured-vuggy space configuration. Restricted by various factors, such as seismic identification accuracy, a static connectivity study can hardly determine the filling and half-filling inside the channel effectively, even if it can identify the main connectivity channels. An injection-production response analysis based on dynamic production data can more accurately reflect the reservoir’s actual connectivity and degree of filling. This paper further studies dynamic response characteristics based on multifractals combined with production data. To reduce the evaluation uncertainty, we combined the static and dynamic connected analysis results to comprehensively evaluate the main connected modes, such as large fracture connectivity, cavern connectivity, and fractured-vuggy compound connectivity. We use the Tahe oilfield as an example to carry out an automatic evaluation of the connected pattern. The comprehensive evaluation results of the new algorithm were basically consistent with the tracer test results and can better reflect the interwell space-configuration relationship. Our model has certain guiding significance for the adjustment of working measures during waterflooding in fractured-vuggy reservoirs.

Characteristics and Seismic Identification Mode of Ultra-Deep Carbonate Fault-Controlled Reservoir in Northwest China

Ordovician carbonate reservoirs in the Shunbei area of the Tarim Basin are characterized by large burial depth, small vertical fault displacement of the strike-slip fault zone, small karst development scale, strong reservoir heterogeneity, complex and diverse seismic reflection types, which lead to unclear seismic response characteristics of fault zone and reservoir, and further restrict the fine description of ultra-deep (>7300 m) fault controlled reservoirs. On the basis of high-precision 3D seismic data analysis, combined with drilling, logging, and comprehensive geological interpretation data in the Shunbei area, seismic geological models of different types of reservoirs and fault zones are established. The changes in seismic response characteristics of fault zones and reservoirs are simulated and analyzed by changing reservoir size, scale, fault and fracture cavity combination modes, as well as other factors. On this basis, two seismic identification models of fault-controlled reservoirs in the Shunbei area are summarized and established. The seismic identification mode of seismic reflection marker wave of fault-controlled reservoir is mainly “fault seismic response characteristics & weak reflection” and red trough anomaly under T74. The internal seismic identification modes are mainly “fault seismic response characteristics & random reflection”, “fault seismic response characteristics & beading”, “fault seismic response characteristics & linear weak reflection”, and “fault seismic response characteristics & random reflection”. Among them, except for “fault seismic response characteristics & random reflection”, the coincidence rate of reservoir prediction of other three types of seismic response characteristics is more than 70%. The coincidence rate of the other three types of seismic response characteristics of a reservoir is more than 70%. The research results provide a reference for the prediction and description of ultra-deep carbonate fault-controlled reservoirs.

Analysis of AVAZ Seismic Forward Modeling of Fracture-Cavity Reservoirs of the Dengying Formation, Central Sichuan Basin

For the purpose of clarifying the seismic response characteristics of fractured-cavity reservoirs of Dengying Formation in the central Sichuan Basin, the paper first intends to establish three geological models of fracture cave reservoirs based on drilling, logging, and core data of the Dengying Formation in the central Sichuan Basin. Then, the formation reflection is calculated with reference to anisotropic Horizontal Transverse Isotropy (HTI) medium. Finally, further research on Amplitude Variation with Azimuth (AVAZ) seismic forward modeling has been conducted to clarify the seismic response characteristics of different reservoir types in the study area. The results suggest that: Seismic response characteristics of fractured-cavity reservoirs are controlled by incident angle and azimuth angle of seismic waves in different types of reservoirs. The incident angle of the seismic wave controls the difference in amplitude caused by different micro-fracture densities, and the azimuth angle controls the identification ability of the micro-fracture direction. The increase in incident angle brings about a gradual decline in amplitude. The magnitude reaches the highest when the azimuth is parallel to the normal direction of the fracture surface; however, it’ll come down to the lowest as the azimuth is perpendicular to the normal direction of the fracture surface. The fracture density fails to affect the amplitude as long as the azimuth angle is parallel to the direction of the fracture. However, the decreased amplitude reflects the increasing fracture density as the azimuth angle is identical to the normal direction of the fracture surface. The comparison between the theoretical model of three different types of fractured-cavity reservoirs and the actual uphole trace shows that the model has high accuracy. The prospect of seismic identification of fractured-cavern reservoirs, based on the results, can provide us with feasible and applicable evidence for future research on seismic identification of reservoirs and prediction of fracture distribution in the Dengying Formation of central Sichuan.

Seismic diagenetic facies prediction of tight sandstone in the offshore sparse well area: An example from the Xihu Depression of the East China Sea Basin

The purpose of this study is to forecast the spatial distribution of diagenetic facies (DF) of tight sandstone in the offshore sparse wells area. Analytical test data, rock physics experiment data and prestack seismic data were used to study the spatial distribution of seismic diagenetic facies (SEISDF) of tight sandstone of the second (H4b) submember of the fourth (H4) member of the Huagang (E3h) Formation in the N gas-field, Xihu Depression, East China Sea Basin. Based on diagenesis and diagenetic minerals, core-based DF of the H4b sandstone were divided into chlorite-coated facies (CHF), calcite-cemented facies (CAF), dissolution facies (DIF), tightly compacted facies (TIF), and quartz-cemented facies (QUF). Various seismic elastic parameters were obtained by prestack elastic parameter inversion method, and sensitive seismic elastic parameters were selected according to the seismic identification principle of DF. In order to predict the spatial distribution of DF, four DF and sensitive seismic elastic parameters were integrated to establish a SEISDF prediction model based on supervised learning, and obtain a diagenetic facies comprehensive index (DFCI) that can distinguish four DF. Then, the 90° phase conversion technique of seismic lithology was used to realize the consistency of the DFCI between isochronous stratigraphic interfaces with core-based DF. The stratal slicing technique of seismic geomorphology was used to make stratal slices of the DFCI between isochronous stratigraphic interfaces. Representative stratal slices were singled out, and the spatial distribution of the SEISDF was interpreted. This study shows that the H4b1 sublayer primarily develops the TIF, while the H4b2 and H4b3 sublayers chiefly develop the QUF, CHF, and DIF. Compared with the H4b2 and H4b3 sublayers, the areas of the QUF and DIF in the H4b4, H4b5, and H4b6 sublayers slightly increase. The QUF are mainly distributed in the subaqueous distributary channel and a small number of sheet sand and channel bar depositional facies in the form of continuous sheets. The CHF are primarily developed in lenticular shape in the channel bar and a small amount of sheet sand and subaqueous distributary channel depositional facies. The most favorable DIF are chiefly developed in the subaqueous distributary channel, channel bar, and sheet sand depositional facies near the fault, which are distributed in strips. This study proposes a very valuable method for the SEISDF prediction of tight sandstone, which can provide a reference for the study of DF of similar strata in other sedimentary basins.

Geoscience Poster G9: Optimising value in the mature Turrum Field: integrating modern seismic, high-resolution sequence stratigraphy and production data in a 3D geological model

Poster G9 The Turrum Field in the offshore Gippsland Basin has been a significant producing field since first development in 2004 and remains a keystone gas resource for the future as many of the Gippsland assets continue to deplete. The Turrum Field is a faulted anticlinal structure with multiple, stacked, Paleocene-aged fluvial to lagoonal reservoirs that stratigraphically sit below the overlying Marlin Field gas cap. This field was developed in two phases with drilling campaigns in 2004 and 2015 and includes a dedicated platform (Marlin B) for the higher pressure, higher CO2 gas. Leveraging the 2018 reprocessed Northern Margins 3D seismic survey with a modern broadband processing workflow and wider bandwidth and higher signal-to-noise ratio has led to a seismic image with greater resolution and allowed improved reservoir characterisation. The uplift in seismic data together with the colour blending capabilities in GeoTeric®, has led to the seismic identification of large-scale fluvial reservoir systems. These products have been integrated with a revised field-wide sequence stratigraphic framework, petrophysical analysis and incorporated into a full-field 3D geological model of the Turrum Field. The resultant geological model has improved our understanding of reservoir connectivity and will enable rapid integration of production and surveillance data to optimise gas deliverability. This will also provide increased confidence for future field depletion planning including the identification of potential bypassed gas opportunities prior to end of field life. To access the poster click the link on the right. To read the full paper click here

Optimising value in the mature Turrum Field: integrating modern seismic, high-resolution sequence stratigraphy and production data in a 3D geological model

The Turrum Field in the offshore Gippsland Basin has been a significant producing field since first development in 2004 and remains a keystone gas resource for the future as many of the Gippsland assets continue to deplete. The Turrum Field is a faulted anticlinal structure with multiple, stacked, Paleocene-aged fluvial to lagoonal reservoirs that stratigraphically sit below the overlying Marlin Field gas cap. This field was developed in two phases with drilling campaigns in 2004 and 2015 and includes a dedicated platform (Marlin B) for the higher pressure, higher CO2 gas. Leveraging the 2018 reprocessed Northern Margins 3D seismic survey with a modern broadband processing workflow and wider bandwidth and higher signal-to-noise ratio has led to a seismic image with greater resolution and allowed improved reservoir characterisation. The uplift in seismic data together with the colour blending capabilities in GeoTeric®, has led to the seismic identification of large-scale fluvial reservoir systems. These products have been integrated with a revised field-wide sequence stratigraphic framework, petrophysical analysis and incorporated into a full-field 3D geological model of the Turrum Field. The resultant geological model has improved our understanding of reservoir connectivity and will enable rapid integration of production and surveillance data to optimise gas deliverability. This will also provide increased confidence for future field depletion planning including the identification of potential bypassed gas opportunities prior to end of field life.

Seismic modelling and observations of rainfall

Rainfall is a key driver of geomorphological processes ranging from impacting drops that lead to the small-scale dislodgement of soil particles to large-scale morphogenic floods and rainfall-induced hillslope processes. Although rainfall has been identified in seismic records, the associated power spectral density and its quantitative relation to the underlying physical processes have not yet been studied. Here, we analyze nearly 2 years of combined seismic and optical disdrometer measurements, where the latter enables the drop-based quantification of rainfall physical properties. Our measurements confirm the broadband observation of ground velocity power spectral density due to rainfall, allowing the seismic identification of rainfall at intensities as low as 1 mm/h. Seismic power, P, shows a power-law scaling with rainfall intensity, I, and kinetic energy, E: P∝I2.1 and P∝E1.6. The observed scaling relations are consistent between the three monitored sites although there are absolute differences in seismic power of about 1 order of magnitude, which are likely due to variability in landcover and subsurface seismic properties. With a physical model, we demonstrate that the observed power-law relations are set by an underlying linear relation between seismic power and rainfall impulse power, and that the associated exponent values of I and E are due to the covariance of the raindrop size distribution with the total number of drops. The largest raindrop fractions, whose relative contribution increases with rainfall intensity, dominate the seismic signal where, in our case, 90% of the seismic power is attributed to drops larger than 3 mm. Using our model, we estimate the contributing area of rainfall to seismic observations to be within a radial distance of ∼5–25 m. The spatially integrated nature of the seismic measurements and their sensitivity to large raindrops, which control the disaggregation and the mobilization of soil particles, make seismic records well-suited for the investigation of soil erosion processes. More generally, our work provides a basis for the temporally-resolved seismic quantification of rainfall that drives the dynamics of various hydro-geomorphological processes.

Deep learning for end-to-end subsurface modeling and interpretation: An example from the Groningen gas field

Subsurface interpretation and modeling are crucial to the success of reservoir exploration and production, which often involves integrating multiple types of subsurface data and accomplishing a series of subtasks consecutively and/or in parallel. Those tasks include data processing and conditioning, structural mapping, property modeling, and others. With the emergence of machine learning (ML), each component of the subsurface modeling and interpretation workflow now has elements of ML automation incorporated into individual steps. However, there have been few attempts to generate an integrated end-to-end workflow that incorporates ML at every stage. This paper presents an end-to-end solution for subsurface modeling and interpretation that is powered by multiple convolutional neural networks (CNNs). Its performance is demonstrated on the Groningen gas field. The workflow can be subdivided into four parts, with the initial phase focusing on data preconditioning, particularly log quality control and reconstruction. Phase two focuses on seismic property estimation (i.e., relative geologic time) and structural feature identification and extraction (i.e., fault and salt). Phase three combines seismic feature extraction, log data, derived seismic properties, and interpretations to generate a 3D rock property model containing modeled gamma ray, density, velocity, and porosity properties. The final component is to validate the estimated subsurface properties by CNN-based seismic image simulation. The results demonstrated in the Groningen field show high accuracy, strong lateral consistency, and a good match with the dominant subsurface features documented in this area, including the Zechstein salt, the complex fault system, and the Rotliegend reservoir model. We conclude that this end-to-end workflow can be readily applied to other fields to provide a one-click solution for efficient subsurface modeling and interpretation.

Tidal sand ridges seismic identification and its application in the Xihu Depression, East China Sea Shelf basin: Enlightenment to hydrocarbon exploration

Tidal sand ridges are the most typical and extensive products of tidal processes and the large-scale layered structures that occur in the coastal area. Although there are abundant sand-riched reservoirs developed in tidal sand ridges, surprising that few people can intuitively identify the distribution in ancient strata. By comparing the seismic microfacies and seismic Root Mean Square Amplitude attribute of high-precision 3-D seismic data, we summarized a new method to identify and describe their superposition and plane distribution. Application examples of the Pingbei Slope Belt in the East China Sea Shelf Basin show the detailed analysis process and the results show that 6 sets of tidal sand ridges have been identified in three intervals of LST, TST, and HST, 5 sets of sand ridges with the same extension direction (342–358°) in LST and HST intervals are obviously affected by tides. This method and application example provides a new meticulous process for tidal sand ridges identification according to the superimposition relationship of seismic microfacies and the plane extension direction of the Root Mean Square Amplitude attribute. The seismic microfacies of it is very easy to be distinguished compared to that of other similar sediments and can accomplish the spatial morphology and parameters characterization of tidal sand ridges in ancient sedimentary strata which buried several kilometers depth in a large-scale area. This method is suitable for most sedimentary basins with tidal background, just need the aid of high-precision 3-D seismic data, and provides practical guidance for the petroleum exploration related to sandstone.

Anisotropic Poroelasticity and AVAZ Inversion for in Situ Stress Estimate in Fractured Shale-Gas Reservoirs

Knowledge of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> stress is of great significance for hydraulic fracture stimulating of unconventional reservoirs. Quantitative estimation of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> stress, especially in the far field, is a major challenge. This research mainly focuses on developing a novel Bayesian AVAZ inversion approach to estimate <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> stress of fractured shale-gas reservoirs with horizontal transversely isotropic (HTI) symmetry. Using the generalized Hooke’s law and Schoenberg’s linear slip model, we first deduce the anisotropic horizontal stress equation in an HTI medium formed by a single set of vertically aligned fractures embedded in an isotropic background rock. Based on the critical porosity model, we then obtain the saturated stiffness matrix with vertical effective stress-sensitive parameters and dry fracture weaknesses using the relationship between vertical effective stress and porosity. Combining the scattering function and the perturbed stiffness matrix, we deduce a linearized PP-wave reflection coefficient as a function of fluid bulk modulus, vertical effective stress-sensitive parameter, dry-rock P- and S-wave moduli, density, and fracture density. Finally, we propose a novel Bayesian amplitude variation with azimuth (AVAZ) inversion constrained by the Cauchy regularization and low-frequency regularization to estimate these model parameters, which are further used to calculate <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> stress. The analysis of synthetic data demonstrates that <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> stress can be reasonably estimated even with moderate noise. A field data set test reveals that the inversion results agree well with the well log interpretation, and the proposed approach can generate meaningful results that are useful for seismic identification of potential fracturing barriers during fracturing stimulation of shale-gas reservoirs.

Seismic identification of tight-oil reservoirs by using 3D rock-physics templates

Tight-oil reservoirs are classified as unconventional hydrocarbon resources, having a complex system of pores and cracks and low porosity/permeability. A good pore-crack connectivity is required for hydrocarbon production, but clay minerals filling the pores and throats may hinder the fluid migration. Thus, the combined effects of the pore-crack network and the presence of clay are the main factors controlling the reservoir properties and its storage capacity. In this study, a suite of cores was collected from a reservoir located in the north of the Songliao Basin (China), and establish their microstructure by scanning electron microscopy. Then, ultrasonic experiments were performed under in-situ conditions to analyze the influence of clay minerals and porosity on the elastic waves. The triple-porosity, differential-effective-medium and self-consistent theories were used to calculate the stiffness moduli by considering the effects of pores, cracks and clay minerals, and to analyze the influence of these reservoir properties on the P-wave attributes. According to attenuation, acoustic impedance and phase-velocity ratio, a multi-scale 3D rock-physics template was established. By using the ultrasonic, sonic-log and seismic data, the templates were calibrated and then the reservoir characteristics were estimated. Two 2D seismic lines were considered and the corresponding predicted reservoir properties were compared to the well-log data and the actual production reports, showing that the porosity and clay content predictions are consistent with these data, and that the oil production areas are all located within the high-cracked porous zones. The 3D rock-physics templates can effectively estimate the distribution of high-quality tight-oil reservoirs.

Seismic Identification of Unconventional Heterogenous Reservoirs Based on Depositional History—A Case Study of the Polish Carpathian Foredeep

An integrated geological and geophysical approach is presented for the recognition of unconventional targets in the Miocene formations of the Carpathian Foredeep, southern Poland. The subject of the analysis is an unconventional reservoir built of interlayered packets of sandstone, mudstone and claystone, called a “heterogeneous sequence”. This type of sequence acts as both a reservoir and as source rock for hydrocarbons and it consists of layers of insignificant thickness, below the resolution of seismic data. The interpretation of such a sequence has rarely been based on seismic stratigraphy analysis; however, such an approach is proposed here. The subject of interpretation is high-quality seismic data of high resolution that enable detailed depositional analysis. The reconstruction of the depositional history was possible due to the analysis of flattened chronostratigraphic horizons (Wheeler diagram). The identification of depositional positions in a sedimentary basin was the first step for the indication of potential target areas. These areas were also subject to seismic attribute analysis (sweetness) and spectral decomposition. The seismic attribute results positively verified the previously proposed prospects. The results obtained demonstrate that the interpretation of the Miocene sediments in the Carpathian Foredeep should take into account the depositional history reconstruction and paleogeographical analysis.