Seismic Structural Interpretation Research Articles

2D Seismic Structural Interpretation of Yamama Formation in Al-Fao Area, Basrah, Iraq

A structural study was conducted in Al-Fao area, southeastern Iraq using two-dimensional seismic data. The seismic lines were divided into three surveys (F, Kl, and Sa). Al-Fao is an exploratory area that does not contain any wells; the well information was based on Siba field, located north of the study area. The primary reservoir target in the lower Cretaceous was Yamama Formation. Two reflectors,top and base Yamama Formation are defined using synthetic seismogram in the time domain for Sb well. A top Yamama Formation was defined as Z-crossing, and a base Yamama Formation as S-crossing. The results showed that the strata tended to slope from the south and southwest to the north and northeast, and the area was affected by multiple structural orogenies. Siba field is an elongated fold whose axis extends northeast-southwest; it consists of a structural nose and northeastern dome. The Two-Way Travel Time map showed higher values in the southeast and east, indicating sloping reflectors in those directions. The depth maps of Yamama Formation showed the deepest part in the southeast and east, suggesting a plunging structure in those directions. The study also revealed the presence of numerous closures as structural noses, which could serve as potential structural traps.

Frequency adaptive fault detection by feature pyramid network with wavelet transform

Fault detection is a key step in seismic structure interpretation. Current research has achieved good results in fault detection by using synthetic training data to train deep-learning models. However, there is an inevitable difference in frequency bandwidth between synthetic training data and real seismic data, which makes it difficult for deep-learning models to obtain ideal fault detection results on real seismic data. To solve this problem, the feature pyramid network (FPN) is introduced to obtain multiscale deep-learning features, which can reduce the impact of seismic data frequency bandwidth differences on fault detection. Then, we apply the multiscale wavelet transform to extract multiscale frequency spectral features of the seismic data and combine them with the multiscale deep-learning features through concatenation operation. Furthermore, the seismic data is decomposed into signals with different frequency bands through the wavelet transform, and we use the energy of these signals as the network weights of multiscale mixed features to further improve the frequency adaptability of our method. Based on these works, we not only improve the fault detection effect in a specific work area but also improve the generalization ability of the deep-learning model in different work areas, thus further promoting the application of deep learning in actual production. Compared with the fault detection results by the traditional deep-learning model U-Net and the traditional FPN on multiple real seismic data and synthetic seismic data, experimental results demonstrate the effectiveness of our method.

Structural Interpretations for Zubair Formation in Kumait oil field, Using 3D Seismic Reflection Data, Southern-East Iraq

This study deals with the interpretation of structural 3D seismic reflection of the Kumait oil field in southern Iraq within the administrative boundaries of the Maysan Governorate. Synthetic seismograms are prepared by using available data of the Kt-1 oil field by using Petrel software to define and pick the reflector on the seismic section of the Zubair Formation, Which represents the Cretaceous Age. The study shows that the Kumait structure is an anticline fold. It is thought to be a structure trap caused by the collision of the Arabian and Iranian plates and trending in the same direction as driving factors in the area, which are from the northwest to the southeast, and the overall trend of strata is north and northeast. Seismic structure interpretation results show the top of the Zubair Formation and several structure closures. The stratification Phenomenon of the study area was clear evidence of the existence of closures which are probable to be hydrocarbon traps.

Unsupervised machine learning and multi-seismic attributes for fault and fracture network interpretation in the Kerry Field, Taranaki Basin, New Zealand

Unsupervised machine learning using an unsupervised vector quantization neural network (UVQ-NN) integrated with meta-geometrical attributes as a novel computation process as opposed to traditional methodologies is currently used effectively in the 3D seismic structural interpretation for high-resolution detection of fault patterns, fracture network zones, and small-scale faults (SSFs). This technology has a crucial role in locating prospective well sites and building a 3D structural model while saving time and cost. The innovation of the current workflow involves combining geostatistical and structural filtering, optimal geometrical seismic attributes, UVQ-NN for automatic major faults, fracture network zones, and SSFs volumes extraction due to the unavailability of well logs and cores. To sharpen the fault edges and discontinuities, a steered volume was first extracted. Structural filters were then applied to the 3D volume, first with a dip-steered median filter (DSMF), followed by a dip-steered diffusion filter (DSDF), and finally, both DSMF and DSDF were combined to generate the fault enhancement filter (FEF). After that, optimal geometrical attributes were computed and extracted, such as similarity, FEF on similarity, maximum curvature, polar dip, fracture density, and thinned fault likelihood (TFL) attributes. Finally, selected attributes were inserted as the input layer to the UVQ-NN to generate segmentation and matching volumes. On the other hand, the TFL was used with the voxel connectivity filter (VCF) for 3D automatic fault patches extraction. The results from the UVQ-NN and VCF identified the locations, orientations, and extensions of the main faults, SSFs, and fracture networks. The implemented approach is innovative and can be employed in the future for the identification, extraction, and classification of geological faults and fracture networks in any region of the world.

Role of inherited fault reactivation in accommodating multistage deformation in the southwestern margin of the Ulleung Basin, East Sea (Sea of Japan): Insights from 3D seismic interpretation

The southwestern margin of the Ulleung Basin, the East Sea (Sea of Japan), preserves complex structural and stratigraphic architectures produced by a multistage tectonic evolution in response to the Cenozoic convergence of the Indian and Pacific/Philippine Sea Plates to the Eurasian Plate. However, the origin, geometry, kinematics, and interrelationship of geological structures that evolved through the multistage tectonic deformation remain elusive, particularly regarding the role of structural inheritance in the evolution of the basin. Based on comprehensive 2D and 3D multichannel seismic reflection and well data, we present structural interpretations of regional-scale faults, folds, and growth strata in the southwestern margin of the Ulleung Basin, with a focus on inherited fault reactivation. In addition, a revisited deformation framework is proposed, involving back-arc extension/normal faulting (stage 1: ca. 23 to 15 Ma), positive inversion/reverse faulting (stage 2: 15 to 10.6 Ma), and strike-slip faulting/local transpression (stage 3: 10.6 Ma to present). Here, we illustrate how the reverse reactivation and propagation of segmented NE–SW normal faults and subsequent strike-slip movement have led to the complex structural and stratigraphic architectures presently evident in the study area. Notably, the final overprinting of a strike-slip deformation on the inherited NE–SW faults during deformation stage 3 has caused significantly damaged stepovers and tips, in which secondary faults and folds might control hydrocarbon migration/trapping and leakage. In this context, we suggest that the gentle antiformal Gorae Ⅰ structure is linked in origin to the Gorae Ⅴ structure, bearing a commercially viable gas trap as a detachment fold system formed by local transpression during deformation stage 3. Our comprehensive 3D structural seismic interpretation increases the understanding of Cenozoic multistage deformation, highlighting the impact of different tectonic drivers affecting the eastern marginal sea of the Eurasian Plate.

Formation evaluation utilizing a new petrophysical automation tool and subsurface mapping of the Upper Cretaceous carbonate reservoirs, the southern periphery of the Abu-Gharadig basin, Western Desert, Egypt

The southern periphery of the Abu-Gharadig basin in the Northern Egyptian Western Desert is characterized by some subsurface geological challenges related to the carbonate reservoir's quality, which requires precise petrophysical evaluation and seismic structural interpretation. Therefore, we conducted a subsurface mapping and formation evaluation for the Upper Cretaceous carbonate reservoirs in the Southwest Abu Sennan (SWS) area utilizing seismic reflection profiles and borehole geophysical data. Seismic mapping of the Upper Cretaceous carbonate reservoirs (Abu Roash (AR)/B,/D, and/F) revealed 3-way folds with NE-SW trends divided by NW-SE normal fault trends presenting significant chances for exploration. These closures were filled by hydrocarbons generated from the Jurassic source rocks. Formation evaluation was performed using the new petrophysical tool “Gaialog” which was coded using Python. Petrophysical parameters for the recognized net pay intervals of AR/B, AR/D, and AR/F carbonate reservoirs showed that the effective porosity (φeff: Phie) and the hydrocarbon saturation (Sh) increases towards the East to Southeast direction while the water saturation (Sw) increases to the Northwest of the study area. The highest net pay and the effective porosity were found in the Eastern part of the study area. The study procedures can be applied in neighboring areas to evaluate and understand similar reservoirs.

The Application of Seismic Attributes in Fault Detection and Direct Hydrocarbon Indicator in Tomboy Field, Western-Offshore Niger Delta Basin

Seismic attribute analysis is important in subsurface data interpretation, such as seismic interpretation, which could involve seismic stratigraphic and structural interpretation. This interpretation is often hampered by seismic resolution and, sometimes, human inability to identify a subtle feature on the seismic. These factors have frequently led to the poor seismic interpretation of geologic features. Thus, an integral approach to studying structural patterns and hydrocarbon bearing zones using seismic attributes was carried out on the Tomboy field using 3D seismic data covering approximately 56 km2 of the western belt of the Niger Delta. The seismic volume underwent post-stack processing, which enhanced seismic discontinuities. A deep steering volume was first created, and several dip filters were applied to enhance faults in the study area. After that, curvature and similarity attributes were calculated on the dip-steered and fault-enhanced volume. These calculations show detailed geometry of the faults and zones of subtle lineaments. Six faults (F1, F2, F3, F4, F5 and F6) were identified and mapped. These faults range from antithetic to crest growth faults. Two major growth faults (F5 and F6) were revealed to dip in the northeast to southwest directions. A near-extensive crest fault (F4) appeared beneath the major faults. Although several minor fractures were displayed in the southern and central portions of the crest fault of the dipping seismic data, the southwest (F4) and growth fault, F6, are responsible for holding the hydrocarbon found within the identified closures. Using attributes on the seismic data increased confidence in mapping and interpreting structural features. Furthermore, energy attributes were used as Direct Hydrocarbon Indicators (DHI) to visualize viable areas within the study, which allows a more robust interpretation. Time slices were taken in regions of flat and bright spots. The spectral decomposition attribute was run on these slices to display areas of high amplitude reflection typical of hydrocarbon-bearing regions trapped mainly by regional to sub-regional growth faults. The surface attribute calculated on the generated surface shows that the field is predominantly controlled by faults serving as traps for hydrocarbon.

An integrated study for seismic structural interpretation and reservoir estimation of Sawan gas field, Lower Indus Basin, Pakistan

The information about the subsurface structure, type of fluids present in the reservoir, and physical properties of the rocks is essential for identifying potential leads. The integrated approach of petrophysical analysis, seismic data interpretation, seismic attributes analysis, lithology, mineralogy identification, and Gassmann fluid substitution were used for this purpose. The structural interpretation with the help of seismic data indicated the extensional regime with horst and graben structures in the study area. The two negative flower structures are cutting the entire Cretaceous deposits. The depth contour map also indicate favorable structures for hydrocarbon accumulation. The four possible reservoir zones in the Sawan-01 well and two zones in the Judge-01 well at B sand and C sand levels are identified based on well data interpretation. The main lithology of the Lower Goru Formation is sandstone with thin beds of shale. The clay types confirm the marine depositional environment for Lower Goru Formation. The water substitution in the reservoir at B sand and C sand levels indicated increased P-wave velocity and density. The water substitution affected the shear wave velocity varies slightly due to density changes. The cross plots of P-impedance versus Vp/Vs ratio differentiate the sandstone with low P-impedance and low Vp/Vs ratio from shaly sandstone with high values in the reservoir area. The P-impedance and S-impedance cross plot indicate increasing gas saturation with a decrease in impedance values. The low values of Lambda-Rho and Mu-Rho indicated the gas sandstone in the cross plot.

Analyzing the seismic attributes, structural and petrophysical analyses of the Lower Goru Formation: A case study from Middle Indus Basin Pakistan

The purpose of this research is to delineate the structures of the Lower Goru Formation, investigate fluid properties, and clarify the hydrocarbon-prone areas through seismic attributes analysis. First, the acquired data was matched by the interpretation datum. Structural analysis was done by performing horizon interpretation, fault interpretation, and contour mapping on the C-Interval of the Lower Goru Formation. Hydrocarbon zones were marked with the help of attribute analysis on seismic sections and were justified by petrophysical analysis. An integrated approach such as seismic structural interpretation, seismic attribute, spectral decomposition, and petrophysical analyses was used in current research to better understand geological structure and features. This research showed that normal faults are present in the area showing negative flower structure, horst and graben, and faults oriented north-west to south-east. The contour map shows structural inclination and faults bound closure near well locations. Variance attribute and spectral decomposition attribute were used to verify horizon lineation and fault behavior. Instantaneous amplitude and instantaneous phase attributes justify hydrocarbon bearing zones, and bright spots are present on seismic sections at C–Interval of Lower Goru Formation. Petrophysical analysis of the available wells showed a number of significant hydrocarbon zones having more than 55% of hydrocarbon saturation at the C-Interval of the Lower Goru Formation. The four possible reservoir zones in Sawan-02 well, two zones in Sawan-07 well, and three zones in Sawan-09 well are identified based on well data interpretation. Based on these analyses, the area of interest has a very good reservoir potential, structural closure, and visible bright spots. The current finding of this research will be helpful for future exploration and development of the Sawan area.

Structural deformation characteristics and its influence on shale gas preservation of the Wufeng−Longmaxi Formation in the Wuxi area, Chongqing, China

The Upper Ordovician Wufeng to Lower Silurian Longmaxi Formation has a good material basis for marine shale gas development, and the structural preservation condition is the key factor to control the rich and integrated shale gas reservoirs in the Wuxi area of Chongqing City, China. Based on the seismic-structural interpretation data, combined with the regional structural background and drilling effect, the structural deformation characteristics and shale gas structural preservation conditions are comprehensively analyzed in the study area. The Wuxi area is located at the structural junction of the Sichuan Basin and southern Dabashan along with strong structural deformations. Seven rows of NW to near EW structural belts are mainly developed. The fold styles and fault development degrees of different structural belts are different, and the difference in the structural preservation conditions of shale gas is also obvious. The study results reveal that the shale gas structure preservation conditions of the Wufeng−Longmaxi Formation in the Wuxi area are overall poor and only locally better. The structure preservation conditions for shale gas enrichment and accumulation are divided into four grades, such as the good Class I area, the general Class II area, the poor Class III area, and the very poor Class IV area. Among them, the Heiloumen structural zone and Huangcaoping buried structural zone nearby the Sichuan Basin have good preservation conditions and are classified as the good Class I preservation area. The macroscopic preservation type of shale gas in the Wufeng−Longmaxi Formation of the Wuxi area belongs to the complex structural preservation of the basin margin. Three structural preservation modes of shale gas in the study area have also been confirmed, including the lost destruction type, lost residual type, and trap preservation type. The trap preservation type is more conducive to the preservation of shale gas, which is the most favorable structural mode for shale gas exploration.

Machine learning applications to seismic structural interpretation: Philosophy, progress, pitfalls, and potential

Machine learning applications to seismic structural interpretation: Philosophy, progress, pitfalls, and potential

Deformational pattern and seismogenic potential of the eastern Makran subduction zone

• The Makran subduction zone has an imbricate thrust fault system. • Attribute analyses show Makran turbidities are fractured under high pore pressures . • Lateral continuity is observed in the frontal region via velocity analysis. • Effective friction 0.04–0.12 is required to reproduce the observed fault system. • Splay faults with high uplift values can amplify earthquake related tsunami. In last 500 years, the ∼900 km long Makran subduction zone (MSZ) has hosted 9 M7+ large earthquakes, and 8 of them activated the eastern segment of the fault. The 1945 M 8.1 megathrust event also generated significant tsunami signifying the region as active subduction zone in the world. Here, we investigate the deformation patterns and seismogenic potential of MSZ utilizing detailed seismic data analyses. Mechanical modeling based on limit analysis approach has also been applied to better understand the seismic shaking potential of ongoing deformation and retrieve the associated frictional properties. The seismic structural interpretation illustrates that MSZ has an imbricate thrust fault system. Furthermore, seismic attributes highlight the fractured and high porosity zones, which reduce friction values along the plate interface. The estimated effective friction ( μ e f f ) to slip does not exceed 0.12 along the subduction interface. We found that μ e f f ∼ 0.04–0.12 is required to reproduce the observed fault system. For wedge geometry, we run different simulations to measure the frontal horizontal and vertical slip. Assuming the convergence rate of 3–4 cm/yr, the calculated slip deficit in last 77, 158, and 257 years, after 1945, 1864 and 1765 earthquakes along offshore-ruptured patches of eastern MSZ is 2.31–3.08 m, 4.74–6.32 m, and 7.71–10.28 m, respectively. A frontal uplift ranging from 0.69 ± 0.37 to 3.02 ± 1.45 m can be expected, if the next rupture occurs along the previously ruptured areas, which possess the ability to amplify the water column and generate a large tsunami in the region.

3D fault detection: Using human reasoning to improve performance of convolutional neural networks

Depicting faults in seismic data is one of the key steps in seismic structure interpretation. However, the manual identification of faults is a time-consuming and tedious process. In conventional methods, seismic attributes associated with the reflection continuities or discontinuities of seismic data are extracted for fault detection. In recent years, convolutional neural networks (CNNs) have been introduced to solve geophysical problems. Herein, we have proposed powerful and efficient methods to enhance the performance of CNN-based fault detection. We first introduce human reasoning to improve the performance of a 3D neural network, which is trained with synthetic seismic data. We propose two methods that efficiently use human reasoning. Manually identified faults can be easily added to train an efficient spatial pyramid network (ESPNet) and contextual information can be obtained to improve the continuity of the faults. We propose an unsupervised fault registration framework to fuse the results from commonly used 3D CNNs and ESPNet, which simultaneously preserves high data accuracy and continuity. Furthermore, to use sparse manually identified faults to directly train a 3D CNN, we propose a weakly supervised learning method. Multiple examples find that faults can be more accurately predicted with the proposed methods than with previously established algorithms, including conventional seismic attributes and CNN-based methods.

Enhancing Characterization of Reservoirs Within the Niger Delta Basin Using Integration of Seismic and Well Logs

This research utilized well logs and seismic to unravel the reservoir architecture of a field within the offshore depolbelt of Niger Delta. Gamma ray and resistivity log responses were used for lithology and hydrocarbon reservoirs identifications. The principle of similarity in log signatures was used for correlation across the three studied wells. Pertinent reservoir parameters such as shale volume, effective porosity, permeability, hydrocarbon saturation and water saturation were calculated using well-established equations consistent with the geology. Seismic structural interpretation that will give insight to deformation of the field involves the identification and mapping of faults and horizons from seismic sections. By integrating information from seismic and wells, 3D geological modelling was done using geostatistical methods of Sequential Gaussian Simulation and Indicator. The general stratigraphy of the studied field comprises of intercalation of sands and shales which is typical of Agbada formation. Three reservoirs designated as AA, BB and CC were identified and mapped. Only reservoir CC was laterally continuous across the three wells. Reservoir AA has average shale volume of 13%, effective porosity 26%, hydrocarbon saturation 46% and permeability 1328 mD. Reservoir BB has shale volume of 10%, effective porosity 28%, hydrocarbon saturation 43% and permeability 1616 mD. Reservoir CC has shale volume of 21%, effective porosity 20%, hydrocarbon saturation 89% and permeability 580 mD. Twenty faults comprising of both major and minor faults were mapped. The faults mapped were majorly normal faults. The result of the seismic structural interpretation shows that the probable structures harboring oil and gas are a combination of four-way closure and fault assisted anticlinal structures. The modelling of facies and petrophysical parameters into maps aided the understanding of parameter’s influence on oil and gas production. Reservoir CC has oil and gas in commercial quantities with 2520 MMcf and 622Mbbls respectively. The result shows the reservoir has high performance system and is therefore recommended for development and production. The resulting models will aid placement of production wells and monitoring of future performance of the reservoirs.

Sedimentary bottom simulating reflection muting—A new model of hydrate and fluid redistribution from the Pegasus Basin, New Zealand

AbstractBottom simulating reflections (BSRs) interpreted in seismic data are one of the most used indicators for the presence of gas hydrates. In numerous hydrate provinces, including the Hikurangi margin, east of New Zealand, distinct and anomalous gaps in reflectivity punctuate otherwise continuous BSRs. We undertake a seismic stratigraphic and structural interpretation of a dense grid of two‐dimensional reflection seismic data to investigate possible causes of widespread BSR gaps that occur near the hinge area of synclines. We explain these BSR gaps with a tectono‐sedimentary model where sedimentation into accretionary wedge synclines leads to an upward migration of the base of gas hydrate stability with respect to stratigraphy, causing dissociation of gas hydrates to water and free gas. A trough‐shaped syncline's radially dipping beds promotes along‐strata, upward migration of gas away from the hinge area, incrementally depleting synclinal hinges of gas and resulting in a BSR gap or muted BSR. This model may be applicable to observed gaps in BSRs in tectonically active slope basins worldwide.

Rock physics as a tool for seismic stratigraphy and structural interpretation of late Miocene southwestern Deep Offshore Niger Delta, West African Continental Margin

Rock physics as a tool for seismic stratigraphy and structural interpretation of late Miocene southwestern Deep Offshore Niger Delta, West African Continental Margin

Fine Complex Geological Structure Interpretation Based on Multiscale Seismic Dip Constraint.

With the development of seismic exploration technology, geological structure interpretation has become more and more refined, whereas random noise interference, subsalt weak seismic reflection signals, and other issues are also gradually emerged at the same time, which resulted in traditional geological structure interpretation accuracy reduction only relying on single seismic data. A novel technical process integrated time-frequency decomposition of seismic data, seismic dip constraints, and geological structure interpretation is proposed in this paper which is named multiscale seismic dip constraint geological structure interpretation. The technical process contains five steps which first use the basis tracking spectrum decomposition technology to convert the seismic data into the time-frequency domain and then decompose the raw seismic data into coarse scale, fine scale, and deliberate scale through window and threshold methods. Subsequently, execute local layer dip calculation with Hilbert transform and geological structure interpretation on seismic data of different scale, respectively. At last, perform geological structure attribute fusion to obtain fine geological structure interpretation. Synthetic data test and field data test show that through multiscale time-frequency decomposition, high-frequency noise interference can be removed and the subsalt seismic weak signal can be enhanced, and then, high-precision fine complex geological structure interpretation can be obtained with seismic dip constraint. Therefore, the technical process proposed in this paper is effective and can be widely applied in the interpretation of field seismic data.

Seismic Work Flow Characterizes Deep, Thin Formation Layers Offshore South China Sea

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper OTC 30164, “Deep and Thin Overpressure Reservoir Characterization of Paleogene Wenchang Formation in the Enping 17 Sag of the South China Sea,” by Jun Liu and Yingwei Li, CNOOC, and Donghai Liang, Schlumberger, et al. The paper has not been peer reviewed. Copyright 2021 Offshore Technology Conference. Reproduced by permission. The complete paper describes an integrated work flow for 3D seismic reservoir characterization of offshore deep and thin layers in the Eocene Wenchang formation (WCF) without sufficient well data. The work flow includes seismic data reprocessing, well-log-based rock physics analysis, seismic structure interpretation, 3D simultaneous amplitude variation with offset (AVO) inversion, 3D lithology prediction, and geological integrated analysis. Formation Development and Objectives The Pearl River Mouth basin (PRMB) on the northern continental margin of the South China Sea has undergone multistage extensional rifts. The Enping Sag lies in the Zhu1 depression, north of the PRMB, and consists of three subsags. Enping 17 is the largest and deepest sag, with an area of 550 km2, and the thickness of Eocene sediments is greater than 3000 m. The deep middle Eocene WCF, with gray lacustrine mudstones, is hydrocarbon-rich and is the major source rock in the area. A wildcat well had penetrated the WCF at an area with a vertical thickness of 380 m. During drilling, the mud weight was increased to 1.46 g/cm3 from 4570 m total vertical depth (TVD) downward because of increasing pore pressure and higher background gas abnormalities in the WCF. A high pore-pressure gradient of 14.5 KPa/m was measured by drillstem test (DST) at a depth of 4641.5 m TVD. Under the protection of the high pore pressure, the high-quality reservoir layer from 4642 to 4651 m TVD was encountered with 12% average porosity, 3.6-md permeability, and 47.1% saturation. Although a hydrocarbon sample was not obtained during the downhole test because of technical restrictions of DST in 1985, gas surge and a small amount of gas and condensate oil were observed after the test instruments were pulled to surface. With the subsequent development of field techniques, it was likely that current drilling and DST techniques could achieve productive oil flow in this layer.

Application of 3D Static Modelling in Reservoir Characterization: A Case Study from the Qishn Formation in Sharyoof Oil Field, Masila Basin, Yemen

AbstractThree‐dimensional (3D) static modelling techniques are applied to the characterization of the Qishn Formation (Fm.) in the Sharyoof oil field locating within the Masila basin, southeastern Yemen. The present study was initiated by the seismic structural interpretation, followed by building a 3D structural framework, in addition to analysing well log data and from these, 3D facies and petrophysical models are constructed. In the Sharyoof oil field, the Qishn Fm. exhibits depth values within the range of 400–780 m below sea level, with a general increase towards the SSE. A set of high dip angle normal faults with a general ENE–WSW trend dissect the rocks. The strata are also folded as a main anticline with an axis that is parallel to the fault trend, formed as a result of basement uplift. According to the facies models, the Qishn Fm. comprises 43.83% limestone, 21.53% shale, 21.26% sandstone, 13.21% siltstone and 0.17% dolomite. The Qishn Carbonates Member has low porosity values making it a potential seal for the underlying reservoirs whereas the Upper Qishn Clastics S1A and C have good reservoir quality and S1B has fair reservoir quality. The Upper Qishn Clastics S2 and S3 also have fair reservoir quality, while the Lower Qishn Clastics zone has good reservoir quality. The water saturation decreases towards the west and east and increases towards north and south. The total original oil in‐place (OOIP) of the Upper Qishn clastics is 106 million STB within the S1A, S1C and S2 zones. Drilling of development wells is recommended in the eastern study area, where good trapping configuration is exhibited in addition to the presence of a potential seal (Upper Qishn Carbonates Member) and reservoir (Qishn Clastics Member) with high porosity and low water saturation.

Deep Learning Using Synthetic Seismic Data by Fourier Domain Adaptation in Seismic Structure Interpretation

Deep learning is a data-driven technique that demands network models trained using big datasets. In seismic structure interpretation, it is very difficult, time-consuming, and relatively economic costs to prepare training datasets by directly annotating real seismic data. Seismic convolution method is an efficient way to synthesize seismic data, which can easily and quickly generate large amount of training datasets. However, there are large differences in feature space between synthetic seismic data and real seismic data. That results in the poor performance of network models trained using synthetic training datasets on real seismic data. In this paper, we propose to use Fourier domain adaptation (FDA) to achieve domain transfer. First, amplitude spectrum of synthetic seismic data is replaced with those of real seismic data to make feature space mapping. Then synthetic seismic data is used for transfer training of network models to improve its performance on real seismic data. The experimental results demonstrate that the FDA performs the domain transfer of synthetic seismic data to real seismic data, which improves the generalization of network models trained based on synthetic seismic data. Meanwhile, the FDA is a promising method for deep learning model transfer training in seismic structure interpretation.