Reservoir Prediction Research Articles

Correlation and sequence stratigraphic interpretation of the lithostratigraphic Snake Cave Interval: Implications for hydrocarbon reservoir prospectivity between the southeast Blantyre and northwestern Neckarboo Sub-basins, Darling Basin, southeastern Australia

Correlation and sequence stratigraphic interpretation was conducted on the upper Lower through upper Middle Devonian sandstones of the Snake Cave Interval succession between the southeast Blantyre and northwestern Neckarboo sub-basins across the central Darling Basin. This article necessitated the definition and use of many sedimentary lithotypes related to different facies associations and depositional environment criteria for the purpose of establishing the sequence stratigraphy to aid hydrocarbon exploration of the studied areas. The data set used a combination of wireline logs, core/cutting data and analysis of the paleo-environments of sedimentary facies from three wells. The sedimentological analysis showed that the Snake Cave Interval section presents three different facies associations, which are visible in both vertical and lateral successions, and are characterised as: meandering and braided fluvial facies associations with minor fluvio-shallow lacustrine complex facies associations. The Snake Cave Interval section in the studied areas is consistently defined by six third-order depositional sequences informally named SCS1, SCS2, SCS3, SCS4, SCS5 and SCS6 in the Nyngynderry-1 and Mount Emu-1 exploration wells, and the Kewell East-1 stratigraphic well. All the stratal patterns in the internal sequence stratigraphic units are asymmetric and marked by lowstand, transgressive and highstand systems tracts separated by sequence boundaries, maximum flooding surfaces and transgression surfaces with unique gamma-ray log response characteristics calibrated by particular lithologic aspects. These are all incorporated within the sequence stratigraphic approach to hydrocarbon reservoir prediction. The stratigraphic architecture of the third-order depositional sequences presented here in our study has implications for the hydrocarbon potential of sandstone reservoirs in the southeastern Darling Basin including the Snake Cave Interval succession targets.

Formation Mechanisms and Distribution Law of Effective Volcanic Reservoirs -- Taking Carboniferous Volcanic Reservoirs in Malang Depression of Santanghu Basin as an Example

The understanding of the formation mechanisms of volcanic reservoirs can provide a reference for the distribution law of effective volcanic reservoirs and oil and gas reservoirs, and has an important guiding role in accelerating the pace of the exploration and development of volcanic reservoirs. Using the data of three-dimensional seismic interpretation, logging, core description and thin section identification, it is concluded that the formation of volcanic reservoirs in Santanghu Basin was controlled by many factors such as tectonics, lithology, lithofacies, fluids, volcanic apparatus, weathering and leaching, including fault rebuilt, unconformity, alkali metasomatism, dissolution, weathering and leaching and other formation mechanisms, 5 types of reservoir formation models are obtained according to the different superimposition modes of the depth mechanism for the formation of volcanic reservoirs in different periods, and five types of distribution law of effective volcanic oil and gas reservoirs are summarized from the understanding of reservoir types, accumulation models, and accumulation mechanisms. The study provides a reference for the prediction of effective volcanic reservoirs, and further defines the exploration direction of volcanic oil and gas reservoirs.

Pore fluids evolution in the sandstone of rift basins: a case study of Dongying sag, Jiyang depression, East China

Pore fluids in basins control the migration of material and energy in sedimentary basin. Make sure pore fluids evolution process would be important for high-quality reservoir prediction. In this study, we pay attention on Dongying sag, which located in the eastern of Jiyang depression, Bohai Bay basin. We collected core sample for thin section observation and SEM, to determine diagenetic sequence in sandstone of study area. Take geological characteristics of study area into consideration, make sure the source of diagenetic products. At last, we deduce the pore fluids evolution process in study area.

Mathematical modelling of carbonate reservoir dissolution and prediction of the controlled hydrochloric acid treatment efficiency

The article presents the theoretical studies results of hydrochloric acid compositions filtration in carbonate collectors porous media saturated with two-phase formation liquid. Solution of filtration problem in the process of carbonate rock leaching with possible regulation of process by hydrocarbon solvents is considered. Numerical algorithm of acid effect on oil-saturated formation is proposed and tested, which allows to determine the following parameters of filtration flow: concentration of hydrochloric acid, distribution of water saturation, pressure and other parameters. A mathematical model of the carbonate collector dissolution process using composite solvents has been developed, which allows predicting technological indicators of acid impact efficiency.

Seismic attributes for characterization and prediction of carbonate faulted karst reservoirs in the Tarim Basin, China

An ultradeep, faulted karst reservoir of Ordovician carbonate was discovered in the Shunbei area of the Tarim Basin. Fractured-cavity reservoirs buried beneath the large thickness of upper Ordovician mudstone were formed along the fault-karst belts. The hydrocarbon accumulation in these reservoirs is controlled by the fault system, and the oil-gas accumulation was affected by karstification and hydrothermal reformation. Previous studies and 2D modeling revealed that the reservoirs had “bright spot” amplitude responses like “string beads,” and they have developed along the strike-slip faults. However, describing such a complex fault-controlled karst system is still a difficult problem that has not been well addressed. We have sought to instruct the attribute expression of faulted karst reservoirs in the northern part of the Tarim Basin. We applied coherence and fault likelihood (FL) seismic attributes to image faults and fractures zones. We then used a trend analysis method to calculate the residual impedance from the impedance of the acoustic inversion, using the fact that residual impedance has higher lateral resolution in reservoir predictions. Finally, we integrated the coherence, FL, and residual impedance attributes into a new seismic attribute, the “fault-vuggy body,” with a certain fusion coefficient. The fault-vuggy body attribute establishes a connection between faults and karst cavities. This method could help in the characterization and prediction of carbonate faulted karst reservoirs. Available drilling data were used to validate that the fused fault-vuggy body attribute was an effective reservoir prediction method. As the seismic sections and slices along the layer help delineate, the distribution of bright spots and strike-slip faults indicates that the main strike-slip fault zones are the most favorable reservoirs in the Shunbei Oil and Gas Field.

Semi‐supervised deep autoencoder for seismic facies classification

ABSTRACTFacies boundaries are critical for flow performance in a reservoir and are significant for lithofacies identification in well interpretation and reservoir prediction. Facies identification based on supervised machine learning methods usually requires a large amount of labelled data, which are sometimes difficult to obtain. Here, we introduce the deep autoencoder to learn the hidden features and conduct facies classification from elastic attributes. Both labelled and unlabelled data are involved in the training process. Then, we develop a semi‐supervised deep autoencoder by taking the mean of intra‐class and the whole population of facies into account to construct a classification regularization term, thereby improving the classification accuracy and reducing the uncertainty. The new method inherits the profits of deep autoencoder and absorbs the information provided by labelled data. The proposed method performs well and produces promising results when it is used to address problems of reservoir prediction and facies identification. The new method is evaluated on both well and seismic data and compared with the conventional deep autoencoder method, which demonstrates its feasibility and superiority with respect to classification accuracy.

Sedimentology, petrography, hydraulic flow units, and reservoir quality of the bayhead delta reservoirs: Late Messinian Qawasim formation, Nile Delta, Egypt

Bayhead sandstone reservoirs are challenging due to their complexities and limited examples. This paper focused on the characteristics of the bayhead sandstone reservoirs and their heterogeneities based on an integrated sedimentological, petrographical, and petrophysical aspects that controls the exploration and development for these reservoirs. This study uses an example from Manzala Gas Field (Eastern Nile Delta). In this study, the sedimentological and petrographical analyses are employed to understand the internal textures and architecture as well as meso- and microscopic heterogeneities of the bayhead delta reservoirs. This is integrated with the petrophysical characteristics and neural network techniques to characterize hydraulic flow units of bayhead delta reservoir using core, borehole image, and log data. The bayhead delta (bay fill) reservoir consists of five main sedimentary sub-environments include main distributary channel, proximal and distal crevasse splays, and crevasse channels, as well as bayhead delta lobes. The distributary channel represents the highest reservoir quality (units 3 and 4), followed by crevasse channel (unit 3 and 2); bayhead delta front lobes (units 2 and 1), and the lowest quality crevasse splays (unit 1). On microscale, the bayhead delta reservoir is characterized by wide spectrum of lithofacies from quartz arenite to feldspathic wacke. The depositional setting is important controlling factor on the reservoir quality that altered by the diagenetic processes. They include the anhydrite, quartz, carbonate, and chlorite, and kaolinite cements as well as dissolution of quartz, feldspar, bioclast, and carbonate grains. This study enhances the understanding of the of the bayhead distributive system heterogeneities and prediction of bay fill facies reservoirs to improve the exploration and development of that targets.

Prediction of Heavy Oil Steam Stimulation Based on Data-Driven and Mechanism Model

In the middle and late stages of heavy oil development, formulating a scientific and reasonable mining plan is the key to improving oilfield efficiency. At present, steam stimulation is still the main development method of heavy oil. The determination of its production is not only limited by boiler conditions, surface pipelines, and wellbore conditions but also by the steam absorption capacity of the formation. Therefore, local analysis cannot achieve the best effect in the whole process of steam stimulation. The mechanism model is the most commonly used method to predict heavy oil production, but too many idealized assumptions make the prediction results quite different from the actual production situation. With the rapid development of machine learning, people can achieve rapid prediction of production through field data. However, when the range of the actual parameter is small, the generalization ability of the model is weak and overfitting occurs. Based on the above background, this paper conducts a coupling study on surface steam pipeline flow, steam injection wellbore flow, and formation flow from the perspective of data-driven. Firstly, based on the correlation coefficient and the feature selection of Random Forest, the importance of the characteristics affecting liquid production and water content was ranked. Secondly, through the comparison of five typical machine learning algorithms, we select the optimal prediction model and optimal characteristics suitable for the sample of this paper. Finally, because of the poor generalization ability of the prediction model, we sampled the mechanism model and increased the diversity of steam dryness samples. We find that the accuracy of the optimal prediction model is improved and the generalization ability of the model is improved after the training of new samples. This paper provides a new idea for the production prediction of heavy oil steam stimulation reservoirs, which is helpful for the efficient development of heavy oil reservoirs.

The technology of effective reservoir prediction in fault development zone

Reservoir prediction in the middle and late stages of development is not only to predict the sandstone, but also to define the specific location of Petroleum-bearing sandstone. The post-stack seismic data is superimposed on a multi-channel seismic data level, although the signal-to-noise ratio is improved to a certain extent, the average amplitude value is obtained in the superposition process, so that only the effective prediction of the sand body can be realized. However, the pre-stack seismic data can obtain the information of shear wave by the longitudinal wave. The characteristics of the shear wave that cannot propagate in the fluid can effectively predict the reservoir and fluid distribution. In order to further quantify the remaining oil potential in fault area, prestack seismic inversion technology and petrophysical analysis are used to determine the favorable oil-bearing area. On this basis, prestack geostatistical inversion is completed to further clarify sand body with high oil saturation. Combined with numerical simulation, it effectively predicts the residual oil distribution at the edge of fault and the precision of the remaining oil quantitative characterization results is high. The recognition rate of thick layer saturation is more than 90%, and the recognition rate of thin interlayer saturation is more than 70%, which can meet the demand of fine reservoir prediction.

Water Cone Dynamic Prediction of Bottom Water Reservoir Considering Oil-Water Interface Dynamic Chance

Water Cone Dynamic Prediction of Bottom Water Reservoir Considering Oil-Water Interface Dynamic Chance

Application of multi-wave and multi-component seismic data in the description on shallow-buried unconsolidated sand bodies: Example of block J of the Orinoco heavy oil belt in Venezuela

The use of multi-wave and multi-component seismic information for reservoir prediction and characterization has been a popular research direction. The study area is located in the Orinoco heavy oil belt in Venezuela. The reservoir is a braided river delta plain deposit and the sandstone is shallowly buried and unconsolidated. Thereby, it is difficult to predict and characterize the type of reservoir effectively with seismic data of conventional P-waves. Based on multi-wave and multi-component seismic acquisition data, the study has conducted petrophysical analysis and seismic horizon calibration with converted wave (PS). Vertically, superimposed sand bodies were identified with PP wave because the PP wave has higher vertical resolution than that of PS wave. Laterally, sectional morphology and plane distribution scale of sand bodies were delineated by using the higher lateral resolution of PS wave. By combining the characteristics of PP wave and PS wave, five models for intersection and sand body superposition were summarized and the architecture units of sand bodies were divided. The seismic attribute (RMS amlpitude) boundary characteristics and continuity of the high amplitude region described by PS wave are more evident to obtain plane distribution of channel bars and braided channels. Three different seismic inversion results of seismic impedance, density and sand thickness from three different methods were compared. The average accuracy of sand body prediction with the method of PP-PS wave combined pre-stack inversion reached approximately 85% which is greater than that of the PP wave post-stack inversion and PP-PS combined post-stack inversion, with accuracy of 64% and 66% respectively. The research results showed that in the study area, the combination of multi-wave and multi-component seismic reflection information can effectively identify and predict multi-stage superimposed sand bodies with clearer vertical superposition and more accurate lateral boundary. Due to the inherent non-uniqueness of seismic information on predicting reservoir distribution, the resolution of seismic data and the difficulty of identification of the highly superimposed shallow-buried unconsolidated sandbodies, reservoir prediction uncertainty still exists. In particular, the interpretation on the sedimentary microfacies distribution and sand-body scale may only be one of the relatively reliable interpretation schemes.

Depositional facies and diagenesis of the Lianglitage Formation in northwestern Tazhong Uplift, Tarim Basin, China: implications for the genesis of ultra-deep limestone reservoir

The limestone reservoir beds of Late Ordovician Lianglitage Formation are preserved in northwestern Tazhong Uplift of the Tarim Basin with buried depth exceeding 6000 m. The origin of the ultra-deep limestone reservoir is still controversial, which restricts the further hydrocarbon exploration. In order to clarify the main controlling factors of reservoirs, we carried out the study of sedimentary facies, diagenesis, and reservoir characteristics based on seismic, well logging, and core data. The Lianglitage Formation in northwestern Tazhong Uplift is mainly composed of nine lithofacies that are deposited from platform margin reef-shoal, platform-interior shoal, and restricted lagoon to tidal flat environments. The Lianglitage Formation has experienced syndepositional submarine diagenesis, penecontemporaneous diagenesis, and burial diagenesis, and consequently the reservoir space in the formation mainly includes fractures and dissolution vugs and caves. Reef and shoal deposits are the material basis of favorable reservoirs, and the favorable reservoirs have been mostly improved by the dissolution of meteoric water in penecontemporaneous diagenesis. In the burial stage, the early-formed porosity was destroyed by cementation to some extent, but the fractures and associated vugs formed in the late Ordovician and Silurian-Devonian played an important role in the improvement of the reservoir. The results are of great significance to the prediction of deep carbonate reservoirs and the hydrocarbon exploration in basins of western China. Favorable facies, early-stage improvement by meteoric water, and tectonic fracture are key to the formation of high-quality large-scale deep limestone reservoirs.

Reservoir Characterization Using Multi-component Seismic Data in a Novel Hybrid Model Based on Clustering and Deep Neural Network

Effective use of the difference between longitudinal and converted shear waves in reservoir sensitivity analysis is a key component to reduce the multi-solution problem of using longitudinal waves only in reservoir characterization. Deep neural network (DNN) is proven to be a powerful tool to solve an end-to-end task in a purely data-driven way, which brings a promising potential in reservoir characterization applications. In this paper, we design a reservoir prediction method using cluster analysis and DNN method. Seismic attributes sensitive to oil and gas responses are first optimized by cluster analysis, and then, a multi-component composite operation is carried out on the optimized attributes to extract oil and gas characteristics. Finally, the DNN is tested and trained to determine the best network model. The final DNN model is further examined using multi-component data in the Fenggu structural area (Sichuan, China) for seismic gas reservoir prediction. The results show that the seismic gas reservoir distribution predicted using this scheme is generally consistent with actual drilling information. Compared to single-component data, the multi-component composite seismic attributes trained network provides prediction results with higher accuracy and reduces the uncertainty of inversion results.

Application of high frequency lake level change in the prediction of tight sandstone thin reservoir by sedimentary simulation

The reservoir distribution of block X in Ordos Basin is mainly controlled by the lake level change. The frequent rise and fall of lake level results in the thin interbedded reservoir. Because the seismic data is not sensitive to tight sandstone and it is difficult to predict thin reservoir, this paper uses the Sedimentary Simulation Technology Based on the principle of sequence stratigraphy to predict thin reservoir in the study area. In the process of sediment simulation, the key to this study is to obtain the accurately high-frequency lake level change curve (The frequency of curve is consistent with that of logging, which depends on the number of vertical grids in the process of sedimentary simulation) and reflect it in the model. Because there is only one well in the study area and the data is relatively scarce, the conventional analysis and test data are difficult to provide the characteristics of lake level change. Therefore, this paper uses the INPEFA (Integrated Prediction Error Filter Analysis) technology to analyze the high frequency lake level change. Through the INPEFA processing of GR curve, the obtained lake level change has a clear trend of change, which can directly see the macro change of lake level and the secondary change of lake level in the stratum. On the premise of obtaining the high frequency lake level change curve, in order to ensure that the simulation results can reflect the characteristics of thin layer, combined with the formation thickness and the high frequency lake level change curve, the vertical step size is refined (refined to 60), and the sedimentary simulation is carried out. The simulation results show the characteristics of high resolution, the thin layer is in good agreement with the logging results, and the change of sandstone caused by the secondary rise and fall of lake level is also well reflected in the model. According to the characteristics of tight sandstone reservoir, the high-quality reservoir prediction is carried out by using the simulation results, which provides a new idea for tight sandstone exploration in this area.

Petrographic features and diagenetic alteration in the shale strata of the Permian Lucaogou Formation, Jimusar sag, Junggar Basin

Reservoir quality is the key parameter controlling shale oil enrichment. However, the complicated lithofacies, which control diagenesis, result in reservoir heterogeneity in the shale strata, creating challenges for reservoir prediction. Combining with the detail analysis of inorganic and organic geochemistry, characteristics of the main lithofacies and diagenetic alteration were investigated in Permian Lucaogou Formation, Jimusar sag, Junggar Basin. Laminated rocks with laminae combinations containing pyroclastic and terrigenous clastic laminae, terrigenous clastic and dolomite laminae, and pyroclastic and carbonate laminae were identified. Massive rocks mainly includes dolomicrite, dolomitic tuff, silt dolostone, dolomitic siltstone, and tuffaceous siltstone. Feldspar dissolution and carbonate cementation were the two dominant diagenetic types, further causing heterogeneity of the shale oil reservoirs. Feldspar dissolution generally occurred in laminated rocks containing pyroclastic laminae with low content of carbonate minerals (PL1), as well as in their adjacent interbedded siltstones. Carbonate cementation generally occurred in laminated rocks containing carbonate laminae, as well as in their adjacent interbedded siltstones. Whether in laminated and massive rocks, sparry carbonate crystals were also precipitated adjacent to organic matter and in microfractures. In the burial processes, enriched transition metal elements of V and Ti in pyroclastic laminae promote catalytic pyrolysis of organic matter. Abundant CO 2 produced during the catalytic pyrolysis promoted feldspar dissolution. Dissolution of sedimentary carbonate minerals by organic acids and CO 2 provided the material sources for secondary carbonate cements. It promoted the recrystallization and re-precipitation of sparry carbonate crystals adjacent to organic matter and in the terrigenous clastic laminae or interbedded siltstones. Ca 2+ , Mg 2+ Sr 2+ , Fe 2+ , and Mn 2+ produced by the transformation of smectite to illite in the pyroclastic laminae also provided Ca source for secondary carbonate cements. External diagenetic fluids providing materials along microfractures is another genesis of carbonate cements in the Permian Lucaogou Formation. • Petrographic features in the shale strata in Permian Lucaogou Formation were identified based on in situ analytical method. • Differential feldspar dissolution and carbonate precipitation generally occurred in different lithofacies. • Catalytic pyrolysis of organic matter in presence of transition metal elements in pyroclastic laminae promoted dissolution. • Development of carbonate cements in the shale strata were mainly provided by three material sources.

Formulating the history matching problem with consistent error statistics

It is common to formulate the history-matching problem using Bayes’ theorem. From Bayes’, the conditional probability density function (pdf) of the uncertain model parameters is proportional to the prior pdf of the model parameters, multiplied by the likelihood of the measurements. The static model parameters are random variables characterizing the reservoir model while the observations include, e.g., historical rates of oil, gas, and water produced from the wells. The reservoir prediction model is assumed perfect, and there are no errors besides those in the static parameters. However, this formulation is flawed. The historical rate data only approximately represent the real production of the reservoir and contain errors. History-matching methods usually take these errors into account in the conditioning but neglect them when forcing the simulation model by the observed rates during the historical integration. Thus, the model prediction depends on some of the same data used in the conditioning. The paper presents a formulation of Bayes’ theorem that considers the data dependency of the simulation model. In the new formulation, one must update both the poorly known model parameters and the rate-data errors. The result is an improved posterior ensemble of prediction models that better cover the observations with more substantial and realistic uncertainty. The implementation accounts correctly for correlated measurement errors and demonstrates the critical role of these correlations in reducing the update’s magnitude. The paper also shows the consistency of the subspace inversion scheme by Evensen (Ocean Dyn. 54, 539–560 2004) in the case with correlated measurement errors and demonstrates its accuracy when using a “larger” ensemble of perturbations to represent the measurement error covariance matrix.

Reservoir hosts prediction for COVID-19 by hybrid transfer learning model

The recent outbreak of COVID-19 has infected millions of people around the world, which is leading to the global emergency. In the event of the virus outbreak, it is crucial to get the carriers of the virus timely and precisely, then the animal origins can be isolated for further infection. Traditional identifications rely on fields and laboratory researches that lag the responses to emerging epidemic prevention. With the development of machine learning, the efficiency of predicting the viral hosts has been demonstrated by recent researchers. However, the problems of the limited annotated virus data and imbalanced hosts information restrict these approaches to obtain a better result. To assure the high reliability of predicting the animal origins on COVID-19, we extend transfer learning and ensemble learning to present a hybrid transfer learning model. When predicting the hosts of newly discovered virus, our model provides a novel solution to utilize the related virus domain as auxiliary to help building a robust model for target virus domain. The simulation results on several UCI benchmarks and viral genome datasets demonstrate that our model outperforms the general classical methods under the condition of limited target training sets and class-imbalance problems. By setting the coronavirus as target domain and other related virus as source domain, the feasibility of our approach is evaluated. Finally, we show the animal reservoirs prediction of the COVID-19 for further analysing.

Diagenesis and fluid evolution in the third member of the Eocene Shahejie Formation, Bonan Sag, Bohai Bay Basin, China

Diagenesis significantly influences sandstone reservoir quality, so that a detailed understanding of diagenesis is essential for the identification and prediction of favorable reservoirs. Several studies have been conducted on individual sandstone reservoirs in the Bonan Sag, a typical half-graben, oil-producing sag in eastern China, but few have explicitly considered the potential impact of the asymmetric shape of the sag, which is steep in the north and gentle in the south. This research takes full consideration of the tectonic setting and distribution of source rocks in the sag to compare the style, magnitude and timing of diagenesis in the northern Steep Slope and Sag Zone (SSSZ) and the southern Gentle Slope Zone (GSZ) by means of drill core observations, thin section petrography, high resolution scanning electron microscopy, fluid inclusion microthermometry, as well as cathodoluminescence and carbonate stable isotope analysis. Petrographic observations identify the wide-spread occurrence of authigenic quartz and clay minerals in association with dissolved feldspar, as well as abundant carbonate cements occurring as several distinct generations due to evolving pore fluid composition. The SSSZ has variable carbonate mineralogy while ankerite dominates in the GSZ. The homogenization temperature of fluid inclusions in authigenic quartz in the SSSZ has a wider range (93°C–157.9 °C) and lower starting temperature (93 °C) compared with the GSZ (106.2 °C) and is characterized by more lighter carbonate δ13C and δ18O values (δ18O: −14.8‰~-11.3‰, δ13C: 1.1‰–2.7‰ for the SSSZ; δ18O: −11.9‰~-5.8‰, δ13C: 2.9‰–5.5‰ for the GSZ). The results indicate that (1) Diagenetic conditions in the Bonan Sag evolved from alkaline to acidic to alkaline in general, but with distinct late stage carbonate cementation in SSSZ vs GSZ; (2) the diagenetic processes as well as the nature of pore waters varied across different zones and also temporally. Acidic conditions in the SSSZ started earlier and persisted for longer than in the GSZ. (3) The regional differentiation of the diagenetic processes and pore fluid evolution result from the source rock distribution and burial histories which differ across the Bonan Sag because of the asymmetric shape of the half-graben. We propose a model of fluid evolution over space and time which may provide a new framework for understanding the diagenetic processes and the fluid evolution of oil-producing sags and also contribute to the prediction of favorable reservoirs.

Main control factors and distribution of carbonate reservoirs in the Hexiwu structural belt

The hydrocarbon accumulation conditions of carbonate buried hills in Hexiwu structural belt are superior, and the hydrocarbon accumulation is controlled by multiple factors such as stratum, structure and reservoir, so it is the focus of oil and gas exploration to find high quality reservoirs. Through the analysis of drilling, logging and core data, it is clear that the carbonate reservoir space in Hexiwu structural belt is mainly composed of intergranular pore, tectonic dissolution fracture and tectonic fracture. Sedimentary facies, diagenesis and tectonic movement are the main controlling factors of carbonate buried hill reservoir formation. The favorable sedimentary facies belt is the foundation of reservoir development, the favorable diagenesis is the guarantee of reservoir development, and the favorable tectonic movement is the key to reservoir development. Through the stratified section to carry out comprehensive reservoir prediction, the accuracy of reservoir prediction results is significantly improved, which provides a foundation for oil and gas development.

Reconstructing drainage pathways in the North Atlantic during the Triassic utilizing heavy minerals, mineral chemistry, and detrital zircon geochronology

AbstractIn this study, single-grain mineral geochemistry, detrital zircon geochronology, and conventional heavy-mineral analysis are used to elucidate sediment transport pathways that existed in the North Atlantic region during the Triassic. The presence of lateral and axial drainage systems is identified and their source regions are constrained.Axial systems are suggested to have likely delivered sediment sourced in East Greenland (Milne Land–Renland) as far south as the south Viking Graben (>800 km). Furthermore, the data highlight the existence of lateral systems issuing from Western Norway and the Shetland Platform as well as a major east-west–aligned drainage divide positioned adjacent to the Milne Land–Renland region. This divide separated the catchments that flowed north to the Boreal Ocean from those that flowed south into a series of endoreic basins and, ultimately, the Tethys Sea. A further potential drainage divide is identified to the west of Shetland.The data presented and the conclusions reached have major implications for reservoir prediction, as well as correlation, throughout the region. Furthermore, understanding the drainage networks that existed during the Triassic can help constrain paleogeographic reconstructions and provides an important framework for the construction of facies models in the region.