Horizon Interpretation Research Articles

Seismogeological interpretation of the wave-reflecting horizons of the eastern side of the transition zone from the South Caspian to the Middle Caspian basin

Seismogeological interpretation of the wave-reflecting horizons of the eastern side of the transition zone from the South Caspian to the Middle Caspian basin

Generating more constrained seeds for seismic horizon extraction

Enhancing accuracy remains the main challenge for the current horizon extraction algorithms. Adding more manually interpreted seeds helps to improve the accuracy of horizon extraction. We intend to generate more seeds prior to the 3D horizon extraction based on seeds that are manually interpreted on the coarse grid of the seismic survey. First, we compute four horizons for the same seismic sequence boundary using deep learning and constrained least-squares algorithms under the constraints of manually interpreted horizon seeds. Next, we generate more seeds by checking the consistency among those four horizons for each seismic trace, and this process is implemented in the same way as the tying loops of manual horizon interpretation. Finally, we extract horizons using constrained least-squares algorithms with the newly computed seeds. The applications of two real seismic surveys demonstrate that our method can generate horizons with higher accuracy when compared with the horizons computed with only manually interpreted seeds.

Blind spectral inversion of seismic data

AbstractReflectivity inversion is a key step in reservoir prediction. Conventional sparse‐spike deconvolution assumes that the reflectivity (reflection coefficient series) is sparse and solves for the reflection coefficients by an L1‐norm inversion process. Spectral inversion is an alternative to sparse‐spike deconvolution, which is based on the odd–even decomposition algorithm and can accurately identify thin layers and reduce the wavelet tuning effect without using constraints from logging data, from horizon interpretations or from an initial model of the reflectivity. In seismic processing, an error exists in wavelet extraction because of complex geological structures, resulting in the low accuracy of deconvolution and inversion. Blind deconvolution is an effective method for solving the problem mentioned above, which comprises seismic wavelet and reflectivity sequence, assuming that the wavelets that affect some subsets of the seismic data are approximately the same. Therefore, we combined blind deconvolution with spectral inversion to propose blind spectral inversion. Given an initial wavelet, we can calculate the reflectivity based on spectral inversion and update the wavelet for the next iteration. During the update processing, we add the smoothness of the wavelet amplitude spectrum as a regularization term, thus reducing the wavelet oscillation in the time domain, increasing the similarity between inverted and initial wavelets, and improving the stability of the solution. The blind spectral inversion method inherits the wavelet robustness of blind deconvolution and high resolution of spectral inversion, which is suitable for reflectivity inversion. Applications to synthetic and field seismic datasets demonstrate that the blind spectral inversion method can accurately calculate the reflectivity even when there is an error in wavelet extraction.

Synchrosqueezing voices through deep neural networks for horizon interpretation

Horizon picking is a crucial element in reservoir characterization, but it remains a labor-intensive process. Manually interpreting horizons across thousands of vertical seismic slices in a 3D seismic survey significantly increases the time and labor required for this task. Although several automated methods for extracting the horizons in seismic images have been developed, their effectiveness can be hampered by interruptions in lateral continuity, such as faults and noise. In addition, closely spaced horizons pose a challenge, making it even more difficult to recognize their exact position. To track the horizons through a 3D seismic volume, other seismic attributes extracted from the 3D seismic data must be used. We suggest using spectral voice components together with the original seismic amplitudes to track the surfaces of the target horizons. We generate the time-frequency spectrum using a high-resolution method, namely the synchrosqueezing wavelet transform (SWT), and the real part of the complex SWT spectrum is the voice component. We import the spectral voice component and the seismic amplitude into a neural network. A deep convolutional neural network is used to track the horizon surfaces within a 3D seismic volume. We evaluate this application on a field seismic data set where closely spaced thin layers are located within a complex faulted formation with noisy seismic data with a low signal-to-noise ratio. The integration of the amplitude and phase within the attribute of the voice component indicates that it improves the quality of the generated horizons, especially compared with using the seismic amplitude only for this task. An example from field data demonstrates the ability of our method to accurately delineate the horizons across fault surfaces and in the immediate vicinity of unconformities. This exceeds the current limits of the existing methods for horizon detection.

An artificial intelligence workflow for horizon volume generation from 3D seismic data

Horizon-based subsurface stratigraphic model building is a tedious process, especially in geologically complex areas where seismic data are contaminated with noise and thus are of weak and discontinuous reflectors. Seismic interpreters usually use stratal (proportional) slices to approximately inspect 3D seismic data along seismic reflectors yet to be interpreted. We introduce an artificial intelligence workflow consisting of three deep learning steps to provide a conditioned seismic image that is easier to interpret, a stratigraphic model that outlines major formations, and moreover a relative geologic time volume that allows us to automatically extract an infinite number of horizons along any seismic reflectors within a seismic cube. Depending on the availability of interpreters, the proposed workflow can either run fully unsupervised without human inputs or using sparse horizon interpretation as constraints to further improve the quality of extracted horizons, providing flexibility in both efficiency and quality. Starting from only seismic images and a few key horizons interpreted on very sparse seismic lines, we demonstrate the workflow to generate a stack of complete horizons covering the entire seismic volume from offshore Australia.

Volumetric Analysis of Selected Reservoirs in Ogbenu Field, Niger Delta, Nigeria Using 3D Seismic and Well Log Data

Volumetric analysis of selected reservoirs in the Ogbenu field, Niger Delta, Nigeria was carried out using 3D seismic and well log data. The objectives include the identification and selection of suitable reservoirs, correlating the reservoirs across the field, generating synthetic seismograms and seismic-to-well ties, performing structural interpretation of faults and horizons to generate time and depth structure map, identifying potential prospects and volumetric analysis to estimate the volume of hydrocarbon in place. The adopted methodology comprises structural, petrophysical and volumetric analysis facilitated by Petrel and Techlog software suites. Well log were utilized to identify distinctive features and cross-well stratigraphic correlation which revealed complex variations, indicating a potential thickening trend in the Agbada sequence towards the southwest. Faults and horizons were mapped to establish the structural framework, unveiling a faulted rollover anticline influenced by lateral fault block movements, contributing to a complex structural style. Detailed analysis of seismic responses, synthetic seismograms, and petrophysical parameters from the well log led to the identifying and correlating of eight prospective reservoir intervals (Reservoir A to H). Average petrophysical parameters, including thickness, porosity, Not-to-Gross ratio, volume of shale, and water saturation were derived from the petrophysical analysis, confirming the eight reservoirs exhibit good petrophysical properties, indicating their potential as promising prospects. The reservoirs exhibit varying qualities, with a southward decline in reservoir quality and indications of gas-water contacts in reservoir A with a similar trend across the other reservoir units. The estimated Original Oil in Place volume were. Reservoir A (29,025.57 MMBOE), B (23.95 MMSTB), C (2,776.37 MMBOE), D (48.19 MMSTB), E (16.69 MMSTB), F (131.98 MMSTB), G (42.19 MMSTB) and H (102.60 MMSTB). This integrative approach revealed complex reservoir variations and structural intricacies, enhancing the understanding of future exploration and production strategies in the Ogbenu field.

What quantum matter tells about quantisation of gravity in a statistical mechanics context

We propose a “guide” towards quantisation of gravity based on quantum matter in a statistical mechanics context. On one hand, a statistical mechanics model naturally arises from the thermodynamic interpretation of horizons in Rindler space. On the other hand, the path integral formulation of quantum field theory can be interpreted from the point of view of statistical mechanics. From these perspectives, gravity and matter are related to each other in the same way as a gas and its chemical potential are. This statistical mechanics interpretation of gravity and matter suggests that gravity should be quantised in a precise way which is determined by the quantisation of matter. Although, in a first step, quantisation of gravity applies for small perturbations of the metric with respect to the vacuum, the most central and general features of quantisation (quantisation prescription, quantum space dimensions) are supported from statistical mechanics and remain valid non-perturbatively.

Reprocessing 2-D airgun seismic reflection data SALTFLU (salt deformation and sub-salt fluid circulation in the Algero-Balearic abyssal plain) in the Balearic promontory and the Algerian basin

In an ever more challenging context for the acquisition of seismic data in the Mediterranean Sea, reprocessing to improve the quality of legacy data has become increasingly important. This work presents the newly reprocessed, open access dataset SALTFLU acquired in the Algerian basin by the National Institute of Oceanography and Applied Geophysics (OGS) in 2012. We apply a ‘broadband’ reprocessing strategy adapted for offset-limited (3 km streamer for a target 4 km below the sea level) airgun reflection seismic data acquired in deep water settings. We then assess if the reprocessed images provide new geological insights on the Mediterranean sub-surface. The workflow relies on an integrated approach combining geophysics and geological interpretation to iteratively build the velocity model. In this way we aim to tackle some of the challenges linked to imaging deep complex geological structures containing high velocity contrasts with 2-D, offset-limited seismic data. We first broaden the bandwidth of the data through multi-domain de-noising, deghosting and a source designature using an operator derived from the seabed reflection. We then perform iterative migration velocity analysis, pre-stack time migration and multiple attenuation in the Radon domain to obtain time-migrated images. The initial velocity model is derived from the resulting time migration velocities, and geologically driven model updates are generated using a combination of travel-time tomography, seismic interpretation of the major salt horizons and velocity gradient flooding. The gradient flooding aims to reproduce the large scale first-order velocity variations, while the travel-time tomography aims to resolve the smaller second-order velocity variations. The results improve our deep geological knowledge of the under-explored Algerian basin down to the base salt and the pre-salt. Fluid indicators are imaged within the Plio-Quaternary of the Algerian basin, which we interpret as thermogenic or biogenic gas sourced from either the Messinian Upper Unit or from the pre-salt, migrating through a hydro-fractured salt. The reprocessed data image lateral and vertical seismic facies variation within the Messinian units that could shed new light on the tectono-stratigraphic processes acting during the Messinian Salinity Crisis. It also reveals numerous previously unresolved volcanic structures within the Formentera basin.

Thermodynamics of the FLRW apparent horizon

To investigate the relationship between gravity and thermodynamics in the case of dynamic systems, we interpret the apparent horizon of the Friedmann-Lemaître-Robertson-Walker (FLRW) spacetime as a thermodynamic system. We derive the corresponding fundamental equation in the entropy representation and explore the consequences of demanding the fulfillment of the classical laws of thermodynamics. We investigate in detail the case of an FLRW spacetime with and without cosmological constant. We show that the interpretation of the apparent horizon as an isolated thermodynamic system is possible only under certain conditions because the analogy is not always valid for all the values of the parameters entering the dynamics of the horizon and certainly not for its entire evolution. Nevertheless, we show that the generalized second law of thermodynamics remains valid.

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 INTERPRETATION OF ASSA-FIELD RESERVOIR IN NORTHERN NIGER DELTA NIGERIA, USING WELL LOG

Structural interpretation and characterization of Assa-field in Northern Niger Delta was done to map the primary structures responsible for hydrocarbon entrapment and closures that are favorable for the accumulation of hydrocarbon as well as to indicate areas for hydrocarbon exploration in the field. The method used for this research involved delineation of lithology, identification of reservoir, interpretation of horizon and fault to generate structural maps of the subsurface. Depth and time structure maps were generated to show more detailed structure of the field. Three major horizons (sand 1, sand 2, and sand 3) were mapped based on uniqueness and clarity of their features. Major faults were delineated from the 3-D seismic section. The appearance of these faults in the field is a sign of possible hydrocarbon accumulation. The knowledge from the results of this study can be applied in exploration and production to identify hydrocarbon trapping potential of a field and volumetric evaluation of fluid in a field.

Spectral Attributes in Onshore Fuba Field Niger-Delta, Nigeria, Using 3-D Seismic Time-lapse Data

Spectral attributes in Onshore Fuba Field Niger Delta, Nigeria, are here presented, using 3D seismic time-lapse data. The FUBA Field lies on latitudes 40 50’58’’- 4 0 55’19’’N and longitudes 60 18’41’’- 6 0 26’41’’E with aerial extent of 840km2 . The base (1997) and the monitor (2009) seismic surveys resulted in a 4D response difference. The Base and Monitor data have a root-mean-square repeatability ratio (RRR) of 0.38 implying a very good repeatability when considering the acquisition, processing and environmental noises. Data processing and interpretation were carried out using Petrel software. Reservoir pressure decline rate of 0.062psi/day resulted in production decline rate of 1192.21bbl/day. Structural interpretation of seismic data reveals a highly faulted field. Two distinct horizons were mapped. Fault and horizon interpretation shows closures that are collapsed crestal structures bounded by two major faults. All the interpreted faults are normal synthetic and antithetic faults which are common in the Niger Delta basin. The depth structure maps reveal anticlinal faults. Reservoirs are found at a shallower depth from 6500 to 7500 ft and at a deeper depth ranging from 11500 to 13000 ft. The variance values range from 0.0 to 1.0. The Variance edge analysis was used to delineate the prominent and subtle faults in the area. The results of spectral decomposition at the different frequencies indicates areas of low frequency and high amplitude associated with known hydrocarbon zones, meandering channels, lobes and the presence of small scale faults in the field. The results of the work will help in the recovery of more hydrocarbon as by-passed zones and subtle structures are revealed in the area of study.

Seismic Attributes for Enhanced Structural and Stratigraphic Interpretation in Onshore Fuba field, Niger Delta, Nigeria

Seismic attributes for enhanced structural and stratigraphic interpretation of Fuba Field, Onshore Niger Delta, Nigeria using Well-log and 3D Seismic data are here presented. Well-to-Seismic ties, faults and horizon mapping, time-surface generation, depth conversion and seismic attributes generation were carried out using Petrel software. The structural interpretation of seismic data reveal highly synthetic and antithetic faults which are in line with faults trends identified in the Niger Delta. Of the 29 interpreted faults, only synthetic and antithetic faults are regional, running from the top to bottom across the field. These faults play significant roles in trap formation at the upper, middle and lower sections of the field. Two distinct horizons were mapped. Fault and horizon interpretation reveal closures which are collapsed crestal structures bounded by these two major faults. The depth structure maps reveal anticlinal faults. Reservoirs are found at a shallower depth from 6500 to 7500ft and at a deeper depth ranging from 11500 to 13000ft. The synthetic and antithetic faults act as good traps for the hydrocarbon accumulation in the study area. The variance and chaos values range from 0.0 to 1.0. The dip magnitude and azimuth values range from 0 to 90 degrees and 0 to 360 degrees. The variance edge, chaos, dip magnitude and azimuth analysis were used to delineate the prominent and subtle faults in the area. The results of spectral decomposition at a frequency of 12-35Hz indicates areas of low frequency and high amplitude associated with known hydrocarbon zones, the presence of channels, lobes and small scale faults in the field. The result of the seismic attribute analysis has shown that the Fuba field has good hydrocarbon prospects.

Identification of Faulting and Structural Styles in the Onshore Fuba field, Niger Delta, Nigeria

Identification of the faulting and structural styles of Fuba Field, Onshore Niger Delta, Nigeria using Well-logs and 3D Seismic data are here presented. Well-to-Seismic ties, faults and horizon mapping, time-surface generation and depth conversion were carried out using Petrel software. The structural interpretation of seismic data reveal highly synthetic and antithetic faults which are in line with faults trends identified in the Niger Delta. Of the 29 interpreted faults, only synthetic and antithetic faults are regional, running from the top to bottom across the field. These faults play significant roles in trap formation at the upper, middle and lower sections of the field. Two distinct horizons were mapped. Fault and horizon interpretation reveal closures which are collapsed crestal structures bounded by these two major faults. The depth structure maps reveal anticlinal faults. Reservoirs are found at a shallower depth from 6500 to 7500ft and at a deeper depth ranging from 11500 to 13000ft. The synthetic and antithetic faults act as good traps for the hydrocarbon accumulation in the study area. The variance values ranges from 0.0 to 1.0. The Variance edge analysis was used to delineate the prominent and subtle faults in the

Hydrocarbon Production Induced Faulting in Onshore Fuba Field Niger-Delta, Nigeria, Using 3-D Seismic Time-lapse Data

Hydrocarbon Production Induced Faulting in Onshore Fuba Field Niger Delta, Nigeria, are here presented, using 3D seismic time-lapse data. The FUBA Field lies on latitudes 40 50’58’’-4 0 55’19’’N and longitudes 60 18’41’’- 6 0 26’41’’E with aerial extent of 840km2 . The base (1997) and the monitor (2009) seismic surveys resulted in a 4D response difference. The Base and Monitor data have a root-mean-square repeatability ratio (RRR) of 0.38 implying a very good repeatability when considering the acquisition, processing and environmental noises. Data processing and interpretation were carried out using Petrel software. Reservoir pressure decline rate of 0.062psi/day resulted in production decline rate of 1192.21bbl/day. Structural interpretation of seismic data reveals a highly faulted field. Two distinct horizons were mapped. Fault and horizon interpretation shows closures that are collapsed crestal structures bounded by two major faults. All the interpreted faults are normal synthetic and antithetic faults which are common in the Niger Delta basin. The depth structure maps reveal anticlinal faults. Reservoirs are found at a shallower depth from 6500 to 7500 ft and at a deeper depth ranging from 11500 to 13000 ft. The variance edge enhanced the faults or sedimentological bodies within the seismic data volume. There are more discontinuities in the difference volume variance edge which implies that there are more cracks in the field of study due to production. The lengths, dips and orientations of the faults and horizons, in the base and monitor stacks, are not equal indicative of faults reactivation that could have resulted from hydrocarbon production. The results of the work can be applied in the hydrocarbon exploitation scheme to minimize the damages associated with production and to ascertain reactivation of faults in the area of study.

Application of Time-Frequency Decomposition and Seismic Attributes for Stratigraphic Interpretation of Thin Reservoirs in Onshore Fuba Field Niger-Delta, Nigeria

Application of time-frequency decomposition and seismic attributes for stratigraphic interpretation of thin reservoirs in Onshore Fuba Field Niger Delta, Nigeria, are here presented, using Well-log and 3D Seismic data. Well-to-seismic tie, fault mapping, horizon mapping, time surface generation, depth conversion and seismic attributes generation were carried out using Petrel software. Structural interpretation of seismic data reveals a highly faulted field. Two distinct horizons were mapped. Fault and horizon interpretation shows closures that are collapsed crestal structures bounded by two major faults. All the interpreted faults are normal synthetic and antithetic faults which are common in the Niger Delta basin. The depth structure maps reveal anticlinal faults. Reservoirs are found at a shallower depth from 6500 to 7500 ft and at a deeper depth ranging from 11500 to 13000 ft. The variance and chaos values range from 0.0 to 1.0. The Variance edge and chaos analysis were used to delineate the prominent and subtle faults in the area while the produced spectra were used to delineate the stratigraphy and thickness of the thin-bedded reservoirs. The results of spectral decomposition at frequencies between 12Hz and 35Hz indicate some thin pay sand zones reservoirs which were characterized by of low frequency and high amplitude associated with known hydrocarbon zones, meandering channels, lobes and the presence of small scale faults in the field. Six new probable zones (Prospects A, B, C, D, E and F) of hydrocarbon accumulation were identified. The results of the study will help in the recovery of more hydrocarbon as by-passed zones and subtle structures are revealed in the area of study.

The Subsurface Structures in Onshore Fuba Field Niger-Delta, Nigeria, Using 3-D Seismic Time-lapse Data

The subsurface structures in Onshore Fuba Field Niger Delta, Nigeria, are here presented, using 3D seismic time-lapse data. The FUBA Field lies on latitudes 40 50’58’’-4 0 55’19’’N and longitudes 60 18’41’’60 26’41’’E with aerial extent of 840km2 . The base (1997) and the monitor (2009) seismic surveys resulted in a 4D response difference. The Base and Monitor data have a root-mean-square repeatability ratio (RRR) of 0.38 implying a very good repeatability when considering the acquisition, processing and environmental noises. Data processing and interpretation were carried out using Petrel software. Reservoir pressure decline rate of 0.062psi/day resulted in production decline rate of 1192.21bbl/day. Structural interpretation of seismic data reveals a highly faulted field. Two distinct horizons were mapped. Fault and horizon interpretation shows closures that are collapsed crestal structures bounded by two major faults. All the interpreted faults are normal synthetic and antithetic faults which are common in the Niger Delta basin. The depth structure maps reveal anticlinal faults. Reservoirs are found at a shallower depth from 6500 to 7500 ft and at a deeper depth ranging from 11500 to 13000 ft. The depth residual maps reveal higher residuals associated with the eastern and western regions which are areas not penetrated by any well. The lengths, dips and orientations of the faults and horizons, in the base and monitor stacks are not equal indicative of faults reactivation that could have resulted from hydrocarbon production. The results of this work can be used in reservoir, field and environmental management in the area of study.

A Multi-Task Learning Method for Relative Geologic Time, Horizons, and Faults With Prior Information and Transformer

Horizon extraction and fault detection are essential in seismic interpretation and closely related to each other. Most existing methods tend to deal with these two tasks independently, and may not work well in interpreting seismic images with complex geologic structures. We propose a multi-task learning (MTL) network with two branches to extract all horizons and detect faults simultaneously by estimating a relative geologic time (RGT) map as well as computing a fault map. These two branches share training datasets, feature maps, and network parameters during the training. The RGT estimation branch, constructed with a transformer architecture, is more lightweight compared to previous CNN methods but provides a larger and structure-oriented receptive field to adaptively capture global structural information for estimating a globally optimal RGT map. The fault detection branch is a simple convolutional neural network (CNN) which merges feature maps shared by the transformer and the derivatives of the estimated RGT to compute a fault map. The fault detection branch provides boundary control for the RGT estimation branch while the later provides global constraints for the former to improve its robustness to noise. Note that our RGT estimation by globally fitting all structures in a seismic image is a volumetric horizon interpretation method with which we are able to obtain a whole volume of horizons, all at once, by simply extracting contours of the RGT map. In our method, we further enable convenient human interactions by integrating manually interpreted horizons (or horizon segments) into the network, which imposes expert knowledge on the network to estimate reasonable RGT results from seismic images with complex fault systems, unconformities, and poor data quality. Moreover, when using 3D horizons as constraints, we are able to decompose the computationaly expensive 3D RGT estimation from a seismic volume into independently parallel 2D estimations slice by slice and combine them to obtain a laterally consistent 3D result.

Tectono-Stratigraphic Modeling of the Wildcat Prospect (Gato do Mato), Santos Basin, Brazil Focusing on Presalt Carbonate Reservoirs

The Santos Basin is the largest Brazilian offshore basin and is currently the main hydrocarbon producer in the country, comprising an area of approximately 350,000 km2 . Given the importance of understanding and analyzing its carbonate reservoirs (Itapema and Barra Velha formations), a tectono-stratigraphic model of the Wildcat Prospect was created. This area is in the Outer High of the Santos Basin, main region of the presalt carbonate reservoirs in the Santos Basin. The 3D model is focused on the presalt reservoir and the understanding of the main tectonic structures in this area and their relationships that conditioned the carbonate successions deposition. Four steps were followed to analyze the depositional and structural framework and build the tectono-stratigraphic model: (i) generation and analysis of seismic attributes to identify and characterize seismic terminations (erosional truncation, toplap, and onlap), seismic facies (debris, build-ups, platform carbonates, and bottom lake), and assist in the tectono-stratigraphic analysis; (ii) seismic interpretation of horizons and faults, which were used as input for the modeling as surfaces and fault planes, creating compartmentalized blocks; (iii) construction of the stratigraphic column to classify the succession of tectonic and sedimentary events; and (iv) the construction of the model. This study helps to understand the depositional and structural evolution of the presalt and provides a three-dimensional understanding of the influence of faults on the reservoir geometry. Faults influenced the eroded zone observed in the Upper Barra Velha Formation, since this erosion occurs mainly at the edges of the large-throw faults. The build-up seismic facies, the main reservoirs in the study area, have a trend NW-SE to N-S following the large-throw faults.

Getting the most out of a large data set: A case study for a large 3D seismic interpretation project in the Carnarvon Basin, NW Australia

A case study is presented for the seismic interpretation of a 3D seismic reprocessing project covering approximately 7200 km2 within a rift basin setting on the Northwest Shelf of Australia. The area includes two main petroleum plays: the Cretaceous Barrow Group Delta and the fluvio-deltaic Triassic Mungaroo Formation. Multiple 3D surveys of varying vintages were reprocessed to provide a unified continuous data set over the area. Seismic amplitude variation with offset inversions were conducted in time and depth domains to produce acoustic impedance and VP/VS volumes. The use of depth-domain inversion enabled more accurate inversion products to be developed with a large lateral and vertical zone of interest to assist in prospectivity assessments. Project time and cost constraints indicated a traditional seismic interpretation process would be ineffective and inefficient. The workflows applied included optimizations of the initial horizon interpretation to improve efficiency, machine learning (ML)-based automatic fault interpretation to save time, and bulk horizon interpretation for time savings and rapid stratal slicing. Utilizing ML and automated interpretation processes in conjunction with seismic inversion products enabled a full prospectivity assessment to be developed within six months. In addition to completing the work within the available time, the applied workflows allowed for significantly more time to be spent on prospectivity assessment rather than structural and stratigraphic interpretations.