Field Measurements of Rogue Water Waves

For the design and operation of offshore structures, heave motion, airgap, splitting forces as well as bending moments are key parameters to reduce down time and ensure safe operations. The increasing number of reported rogue waves with unexpected large wave height (Hmax/Hs20), crest height (?c/ Hmax0.6), wave steepness and group pattern (e.g. Three Sisters) suggests a reconsideration of design codes by implementing an Accidental Limit State with a return period of 10000 years. For investigating the consequences of specific extreme sea conditions numerical simulations of the seakeeping behavior, including motions and structural forces, as well as model tests have been carried out with FPSOs and semisubmersibles in a reported roguewave, the Draupner New YearWave. Both, frequency and time-domain results are presented. With frequencydomain analysis the profound data for the standard assessment of structures, concerning seakeeping behavior, operational limitations and fatigue are obtained. In addition, time-domain analysis in real rogue waves gives indispensable data on extremes, i.e. motions and structural forces. As the wave/structure interaction is analyzed in deterministic (freak) wave sequences the most critical position is evaluated by systematic simulations, and the causes of (nonlinear) structure response are revealed. Introduction Surviving a freak wave - what an experience. However, only scarce observations are available of such mystic disasters. Reports on individual extreme waves in deep water mention either single high waves or several successive high waves. Fig. 1-Rogue wave observations - Bay of Biscay (top) and Atlantic Ocean South (bottom) 1 Fig. 1 shows two exceptional and frightening events 1. Breathtaking waves have also been presented by Faulkner 2 who proposes the definition Hmax2.4Hs for abnormal wave height. From a probability analysis of rogue wave data recorded from 1994 to 1998 at North Alwyn Wolfram et al. 3 conclude that these waves are generally 50% steeper than the significant steepness, with wave heights Hmax2.3Hs. The preceding and succeeding waves have steepness values around half the significant values while their heights are around the significant height. Registrations of rogue waves are shown in Fig. 2 and 3:a giant wave (Hmax25.63m) with the crest height ?c18.5m hit the Draupner jacket platform on January 1, 19954off Yura harbor in the Japanese Sea a 13.6m wave with ?c 8.2m has been recorded in a sea state of Hs5.09m5 Exceptional waves have also been reported from the Norwegian Frigg field6 - Hs8.49m, Hmax 19.98m,? c_ 12.24m, water depth d=99.4m, as well as from the Danish Gorm Field7 - Hs_ 6.9m, Hmax17.8m, ? c= 13m, water depth d=40m. All these wave data, with Hmax/Hs2.15 and ? c/Hmax0.6, prove that rogue waves are serious events which should be considered in the design process. Although their probability is very low they are physically possible. It is a challenging question which maximum wave and crest heights can develop in a certain sea-state characterized by Hs and Tp. In addition to the global parameters Hs and Tp the individual wave height and shape as well as its effects on a structure depend on superpositions and the interaction of wave components, i.e. on local wave characteristics.

The hurricanes of 2004 and 2005 caused substantial damage even to relatively new deepwater facilities such as Petronius and Pompano. Crest heights calculated using standard theories are unlikely to have caused such damage. Several possible reasons for the discrepancy between crest height calculated by standard methods and observed deck damage ere considered. Freak waves due to unusual wave spectra were not observed at sites where individual waves were recorded. Much of the damage occurred on structures with small members so diffraction was not an issue. Calculations of the maximum crest height over the area of a deck were able to explain the damage. If the an entire deck is inundated, thelateral force on a structure increases greatly. Our calculations how that while local inundation is more likely than previously suspected, the inundation is usually local and does not necessarily threaten the integrity of the structure. Introduction In September 2004, Hurricane Ivan generated the largest waves ever recorded in the Gulf of Mexico. In 2005, Hurricanes Katrina and Rita added to the devastation. Over 100 platforms were destroyed in these storms. Most of them were old, designed to standards that are now obsolete. But the lower decks of many large new structures also suffered damage, casting doubt on present design standards. Figure 1 shows the bent plate girders under the south end of the cellar deck of the Petronius compliant tower after Hurricane Ivan. This damage must have been caused by one or more wave crests striking the girders. The bottom of steel on the cellar deck is at 16.75 m above mean water level and the deck was set down approximately 0.3 m during the storm. The wave crest near the plate girders must have exceeded 16.45 meters above mean water level. Cardone et al. [1] found that the Oceanweather wave hindcast model did a good job of matching significant wave height measurements in Ivan. The purpose of this paper is to determine whether crest heights calculated on the basis of those hindcasts can explain the observed deck damage. The maximum hindcast significant wave height at the Oceanweather grid point closest to Petronius was 14.76 m. According to Forristall's [2] empirical wave height distribution, the highest wave in 1000 would be 24.95 m. The crest height of a Stokes fifth order wave of this height is 13.96 m, far below the height needed to produce the observed damage. As shown in the next section, second order crest height statistics give an estimated maximum crest height about two meters higher, but still too low to explain the damage to the deck. There are several possible explanations for discrepancies between predicted crest heights and observed damage. One suggested mechanism is that unusual directional spectra can increase the chance of freak waves larger than predicted by second order theory. Two inherently contradictory causes of freak waves have been suggested in the literature. The first is crossing seas with very wide directional spreading. The second is related to the Benjamin-Feir instability.

<p><strong>(manuscript accepted into Applied Ocean Research https://www.researchgate.net/publication/344786014)</strong></p><p><strong>Abstract</strong></p><p>Nearly four decades have elapsed since the first efforts to obtain a realistic narrow-banded model for extreme wave crests and heights were made, resulting in a couple of dozen different exceeding probability distributions. These models reflect results of numerical simulations and storm records measured from oil platforms, buoys, and more recently, satellite data. Nevertheless, no consensus has been achieved in either deterministic or operational approaches. Typically, distributions found in the literature analyze a very large set of waves with large variations in sea-state parameters while neglecting homogeneous smaller samples, such that we lack a suitable definition for the sample size and homogeneity of sea variables, also known as sampling variability (Bitner-Gregersen et al., 2020). Naturally, a possible consequence of such sample size inconsistency is the apparent disagreement between several studies regarding the prediction of rogue wave occurrence, as some studies can report less rogue wave heights while others report more rogue waves or the same statistics predicted by Longuet-Higgins (1952), sometimes a combination of the three in the very same study (Stansell, 2004; Cherneva et al., 2005). In this direction, we have obtained a dimensionless parameter capable of measuring how large the deviations in sea state variables can be so that accuracy in wave statistics is preserved.  In particular, we have defined which samples are too heterogeneous to create an accurate description of the uneven distribution of rogue wave likelihood among different storms (Stansell, 2004). Though the literature is rich in physical bounds for single waves, here we describe empirical physical limits for the ensemble of waves (such as the significant steepness) devised to bound these variables within established and prospective wave distributions. Furthermore, this work supplies a combination of sea state parameters that provide guidance on the influence of sea states influence on rogue wave occurrence. Based on these empirical limits, we conjecture a mathematical model for the dependence of the expected maximum of normalized wave heights and crests on the sea state parameters, thus explaining the uneven distribution of rogue wave likelihood among different storms collected by infrared laser altimeters of the North Alwyn oil platform discussed in Stansell (2004). Finally, we demonstrate that for heights and crests beyond 90% of their thresholds (H>2H<sub>1/3</sub> for heights), the exceeding probability becomes stratified, i.e. they resemble layers of probability curves according to each sea state, suggesting the existence of a dynamical definition for rogue waves rather than purely statistical.</p><p> </p><p><strong>References</strong></p><p>Bitner-Gregersen, E. M., Gramstad, O., Magnusson, A., Malila, M., 2020. Challenges in description of nonlinear waves due to sampling variability. J. Mar. Sci. Eng. 8, 279.</p><p>Longuet-Higgins, M., 1952. On the statistical distribution of the heights of sea waves. Journal of Marine Research 11, 245–265.</p><p>Stansell, P., 2004. Distribution of freak wave heights measured in the north sea. Appl. Ocean Res. 26, 35–48.</p><p>Cherneva, Z., Petrova, P., Andreeva, N., Guedes Soares, C., 2005. Probability distributions of peaks, troughs and heights of wind waves measured in the black sea coastal zone. Coastal Engineering 52, 599–615.</p>

Rogue waves are individual ocean surface waves with a height greater than 2.2 times the significant wave height.  They can pose a danger to marine operations, onshore and offshore structures, and beachgoers, especially when encountered in high sea states. The prediction of bulk sea state parameters like significant wave height, period, direction, and swell components is satisfactorily addressed in current operational wave models. Individual wave heights cannot be predicted by those spectral models, and the prediction of rogue wave occurrence has to be in a probabilistic sense.Previous attempts on such a prediction are based on the Benjamin Feir Index (BFI), which reflects the nonlinear process of modulation instability as the dominant generation mechanism for rogue waves. However, there is increasing evidence that BFI has limited predictive power in the real ocean. Recent studies established the average crest-trough correlation as the strongest single variable to correlate with rogue wave probability.We demonstrate that crest-trough correlation can be forecast by an operational WAVEWATCHIII wave model with moderate accuracy. Using multi-year wave buoy observations from the northeast Pacific we establish the functional relation between crest-trough correlation and rogue wave occurrence rate, thus calibrating predicted crest-trough correlations into probabilistic rogue wave predictions. Combined with the predicted significant wave heights we can identify regions of enhanced rogue wave risk. Results from a case study of a large storm off Canada’s west coast are presented to evaluate the regional wave model at high seas, and to present the rogue wave probability forecast based on crest-trough correlation.

Rogue waves are sudden and extreme occurrences, with heights that exceed twice the significant wave height of their neighboring waves. The formation of rogue waves has been attributed to several possible mechanisms such as linear superposition of random waves, dispersive focusing, and modulational instability. Recently, nonlinear Fourier transforms (NFTs), which generalize the usual Fourier transform, have been leveraged to analyze oceanic rogue waves. Next to the usual linear Fourier modes, NFTs can additionally uncover nonlinear Fourier modes in time series that are usually hidden. However, so far only individual oceanic rogue waves have been analyzed using NFTs in the literature. Moreover, the completely different types of nonlinear Fourier modes have been observed in these studies. Exploiting twelve years of field measurement data from an ocean buoy, we apply the nonlinear Fourier transform (NFT) for the nonlinear Schrödinger equation (NLSE) (referred to NLSE-NFT) to a large dataset of measured rogue waves. While the NLSE-NFT has been used to analyze rogue waves before, this is the first time that it is systematically applied to a large real-world dataset of deep-water rogue waves. We categorize the measured rogue waves into four types based on the characteristics of the largest nonlinear mode: stable, small breather, large breather and (envelope) soliton. We find that all types can occur at a single site, and investigate which conditions are dominated by a single type at the measurement site. The one and two-dimensional Benjamin-Feir indices (BFIs) are employed to examine the four types of nonlinear spectra. Furthermore, we verify on a part of the data set that for the localized types, the largest nonlinear Fourier mode can be attributed directly to the rogue wave, and investigate the relation between the height of the rogue waves and that of the dominant nonlinear Fourier mode. While the dominant nonlinear Fourier mode in general only contributes a small fraction of the rogue wave, we find that soliton modes can contribute up to half of the rogue wave. Since the NLSE does not account for directional spreading, the classification is repeated for the first quartile with the lowest directional spreading for each type. Similar results are obtained.

A reanalysis is reported of the wave time series recorded during Hurricane Camille having as objective the identification of individual waves that satisfy current criteria defining abnormal or freak waves. It is shown that during the hurricane development, a very nonstationary situation has occurred during which the second‐order sea state parameters changed significantly with time. The parameters of the largest individual waves in sea states which identify abnormal waves did not show any clear trend, and such waves occurred during the development stage and not when the significant wave height was the largest. It is argued that the present criteria of identification of abnormal waves are not satisfactory, as they do not take into account the nature of the sea states in which the waves occur.

Rogue waves, which are defined as waves with a wave height, or alternatively a crest height, exceeding the significant wave height by a certain factor, continue to endanger ships and offshore infrastructure. Hence, reliable rogue wave forecasting is of utmost importance to increase the safety for maritime operations. While the occurrence of rogue waves is widely acknowledged, their emergence remains unpredictable due to the lack of a well-accepted basis for explaining their occurrence. In fact, two popular mechanisms explaining the formation of rogue waves lead to considerably different conclusions about their predictability. On the one hand, a rogue wave could be formed by a superposition of wave trains with unknown phases. With this generation mechanism, rogue wave prediction is not viable. On the other hand, nonlinear focusing leading to the Benjamin-Feir instability gives rise to slowly developing rogue waves. Hence, this rogue wave formation could be detected with significant advance time. Given this background, there is an imperative need to address the basic question: Are rogue waves predictable? In this article, the authors explore the predictability of rogue waves by constructing and parameterizing neural networks. The networks are trained on available buoy data, which allows not only for an assessment under the most realistic conditions but also for indicating the sufficiency of current ocean measurements for rogue wave prediction.

<p>Rogue waves are abnormally large waves in the ocean that are at least twice as large as their surrounding waves. The present work combines existing data of rogue wave events, which have been reported in mass media sources. These rogue events caused damages of ships, oil platforms, coastal structures, and human losses [1-6]. Evidences of this phenomenon are widely spread around the globe.</p><p>The database includes 431 rogue events registered during the period 2005-2021. The following information about each event is available: data and location, description, reported wave height of the event (not always), damages, link to the source.</p><p>Locations of the events have been determined approximately based on the eyewitnesses’ reports. The water depth for each event has been taken from the GEBCO database. Based on this water depth, all events have been separated into groups based on the depth of their occurrence: deep water (depth is more than 50m), shallow water (depth is less than 50 m), and coast. The latter represented either gentle beaches or high rocky coasts.</p><p>Using the data from global atmospheric and ocean reanalysis ERA5, the characteristics of background waves and maximal individual waves in the area as well as meteorological conditions have also been determined and analyzed. This includes wind speed, gust, significant wave height, maximum individual wave height, peak wave period, and spectra. According to these data, the freak events that satisfy the criterion of modulation instability <em>kh</em>>1.363 (where <em>h</em> is the water depth and <em>k</em> is the wave number) have been distinguished.</p><p>According to the events’ descriptions and ERA5 information, all rogue wave events have been divided into two groups: “true” and “possible”. For true events the wave description satisfies the freak wave conditions: to be unexpected and abnormally high – twice larger than the background waves. The events, which could not be classified with certainty as “true” due to the lack of data, but which could still be related to rogue wave events, have been considered as “possible”.</p><p>Based on the available data the conclusions about characteristics of a rogue wave, associated to accidents, their occurrence, and their statistics are drawn.</p><p>This work was supported by the Russian Science Foundation (project No. 21-77-00003).</p><p><strong>Bibliography</strong></p><p>1) Didenkulova I, Slunyaev A, Pelinovsky E, Kharif Ch (2006) Freak waves in 2005. Nat Hazard Earth Syst Sci 6:1007-1015</p><p>2) Nikolkina I, Didenkulova I (2011) Rogue waves in 2006 – 2010. Nat Hazards Earth Syst Sci 11: 2913–2924</p><p>3) O'Brien L, Renzi E, Dudley J M, Clancy C, Dias F (2018) Catalogue of extreme wave events in Ireland: revised and updated for 14680 BP to 2017. Nat Hazards Earth Syst Sci 18:729-758</p><p>4) García-Medina G, Özkan-Haller H T, Ruggiero P et al. (2018) Analysis and catalogue of sneaker waves in the US Pacific Northwest between 2005 and 2017. Nat Hazards 94: 583–603</p><p>5) Didenkulova E (2020) Catalogue of rogue waves occurred in the World Ocean from 2011 to 2018 reported by mass media sources. Ocean and Coastal Management 188: 105076</p><p>6) Didenkulova I, Didenkulova E, Didenkulov O<sup></sup> (2022)<strong> </strong>Freak wave accidents in 2019-2021. Proceedings of OCEANS </p>

Freak or rogue waves are so called because of their unexpectedly large size relative to the population of smaller waves in which they occur. The 25.6 m high Draupner wave, observed in a sea state with a significant wave height of 12 m, was one of the first confirmed field measurements of a freak wave. The physical mechanisms that give rise to freak waves such as the Draupner wave are still contentious. Through physical experiments carried out in a circular wave tank, we attempt to recreate the freak wave measured at the Draupner platform and gain an understanding of the directional conditions capable of supporting such a large and steep wave. Herein, we recreate the full scaled crest amplitude and profile of the Draupner wave, including bound set-up. We find that the onset and type of wave breaking play a significant role and differ significantly for crossing and non-crossing waves. Crucially, breaking becomes less crest-amplitude limiting for sufficiently large crossing angles and involves the formation of near-vertical jets. In our experiments, we were only able to reproduce the scaled crest and total wave height of the wave measured at the Draupner platform for conditions where two wave systems cross at a large angle.

Nearly four decades have elapsed since the first efforts to obtain a realistic narrow-banded model for extreme wave crests and heights were made, resulting in a couple dozen different exceeding probability distributions. These models reflect results of numerical simulations and storm records measured off of oil platforms, buoys and more recently satellite data. Nevertheless, no consensus has been achieved in either deterministic or operational approaches. Moreover, a minor issue with the established distributions is that they are not bounded by more than one physical limit while others are not bounded at all. Though the literature is rich in physical bounds for single waves, here we describe physical limits for the ensemble of waves that have not yet been addressed. As previous studies have shown, the exceeding probability distribution does not depend unequivocally on one sea state parameter, thus, this work supplies a combination of sea state parameters that provide guidance on the sea state influence on rogue wave occurrence. Based on specific bounds, we conjecture the dependence of the expected maximum of normalized wave heights (also known as abnormality index) and crests on the aforementioned sea-state parameters instead of the total number of waves in the wave record. Finally, we introduce a new dimensionless parameter that is capable of explaining the uneven distribution of rogue waves in the different storms pointed out by Stansell [74].

The recent and ongoing expansion of marine infrastructure, including offshore wind farms, oil and gas platforms, artificial islands, and aquaculture facilities, highlights the need for effective monitoring systems. The development of robust models for offshore infrastructure detection relies on comprehensive, balanced datasets, but falls short when samples are scarce, particularly for underrepresented object classes, shapes, and sizes. By training deep learning-based YOLOv10 object detection models with a combination of synthetic and real Sentinel-1 satellite imagery acquired in the fourth quarter of 2023 from four regions (Caspian Sea, South China Sea, Gulf of Guinea, and Coast of Brazil), this study investigates the use of synthetic training data to enhance model performance. We evaluated this approach by applying the model to detect offshore platforms in three unseen regions (Gulf of Mexico, North Sea, Persian Gulf) and thereby assess geographic transferability. This region-holdout evaluation demonstrated that the model generalizes beyond the training areas. In total, 3529 offshore platforms were detected, including 411 in the North Sea, 1519 in the Gulf of Mexico, and 1593 in the Persian Gulf. The model achieved an F1 score of 0.85, which improved to 0.90 upon incorporating synthetic data. We analysed how synthetic data enhances the representation of unbalanced classes and overall model performance, taking a first step towards globally transferable detection of offshore infrastructure. This study underscores the importance of balanced datasets and highlights synthetic data generation as an effective strategy to address common challenges in remote sensing, demonstrating the potential of deep learning for scalable, global offshore infrastructure monitoring.

Rogue waves are ocean surface waves larger than the surrounding sea that can pose a danger to ships and offshore structures. They are often deemed unpredictable without complex measurement of the wavefield and computationally intensive calculation, which is infeasible in most applications; consequently, there a need for fast predictors. Here we collate, quality control, and analyze the largest data set of single‐point field measurements from surface following wave buoys to search for predictors of rogue wave occurrence. We find that analysis of the sea state parameters in bulk yields no predictors, as the subset of seas containing rogue waves sits within the set of seas without. However, spectral bandwidth parameters of rogue seas display different probability distributions to normal seas, but these parameters are rarely provided in wave forecasts. When location is accounted for, trends can be identified in the occurrence of rogue waves as a function of the average sea state characteristics at that location. These trends follow a power law relationship with the characteristic sea state parameters: mean significant wave height and mean zero upcrossing wave period. We find that frequency of occurrence of rogue waves and their generating mechanism is not spatially uniform, and each location is likely to have its own unique sensitivities, which increase in the coastal seas. We conclude that forecastable predictors of rogue wave occurrence will need to be location specific and reflective of their generation mechanism. Therefore, given location and a sufficiently long historical record of sea state characteristics, the likelihood of occurrence can be obtained for mariners and offshore operators.

A monotonic pull test was performed on a driven model pile in a large calibration chamber fried with incremented calcareous sandy silt, prepared as an analogue of material obtained in the vicinity of a new platform in Australia's Bass Strait. A cone electrometer test was performed prior to the installation of the pile. Strain gauges mounted along the pile enabled the evaluation of pile axial loads developed during the pile driving and pull test. INTRODUCTION Calcareous soils are found in many parts of the world where offshore platforms are built, for example Bass Strait and the North West Shelf of Australia, Arabian Gulf, Gulf of Mexico, Mediterranean Sea and the Brazilian Campos Basin. The carbonate formations occur in varying states of cementation, with classification ranging from well-graded sand to silty sand and sandy silt. There is, however, a lack of detailed information on pile behavior during driving and pull testing in the finer materials, and also on the geotechnical characteristics of such materials. As part of an investigation of the behavior of axially loaded driven piles and grouted piles in calcareous soils, a monotonic pull test was performed on an instrumented pile driven into a large calibration chamber filled with calcareous sandy silt. ?Ile soil, designated Soil B, is an analogue of material found in the vicinity of a new platform in Australia's Bass Strait, and was produced by grinding a medium calcareous sand, designated Soil A, dredged from another site in Bass Strait [1]. Descriptions of the cone electrometer, pile driving equipment, model pile, chamber and other associated equipment are given in [1]. This paper describes the characteristics of the test soils, the procedures that were developed to prepare the test sample, and the results of the cone penetration and model pile test that were performed in this soil PROTOTYPE AND ANALOGUE SOIL CHARACTERISTICS The in situ soil to be modeled in this investigation has a particle size distribution of a sandy silt. It is cemented, with typical in situ void ratios of 0.95 ± 0.05. Due to the unavailability of prototype soil to carry out model pile testing, an analogue material (Soil B) was produced by passing Soil A through a variable gap disc mill. Platey shells and elongated and coral fragments were broken down during the milling process. Grain size distribution curves for samples of the product were obtained during the process, and the gap between the discs was adjusted to compensate for disc wear when required. The particle size distribution curve of Soil B is shown in Fig. 1 and the specific gravity was found to be 2.73. It should be noted that the material is extremely fine and to the authors' knowledge, no other model pile tests have been conducted in such fine cohesion less material.

With the effects of time-dependent external potential, we investigate the rogue matter waves in a Bose-Einstein condensate (BEC), which can be described by the quasi-one-dimensional Gross-Pitaevskii (GP) equation. Darboux transformation (DT) with the multi-parameters for the spectral problem is constructed with the help of gauge transformation. Through a generalized DT, the first- and second-order rogue-wave solutions of the GP equation are obtained. Influence of the linear and harmonic potentials on the background density, peak height and width of the rogue wave is discussed. With the presence of the harmonic potential, rogue wave on the periodic and monotonically increasing background is shown, and its peak height and width can be manipulated. With the presence of the linear potential, the background density of the rogue wave is a constant, and peak height and width of the rogue wave keep invariant. Graphic analysis demonstrates that the oscillating behavior and parabolic trajectory of the rogue wave appear in a BEC with the linear potential.

A large quantity of oil and gas resources is reserved in the offshore deepwater basins of the world.The occurrence of high quality reservoirs is the necessary condition for forming large hydrocarbon accumulations.A comprehensive study of 24 key deepwater oil-gas-bearing basins of the world,mainly from the Atlantic deepwater and the Neotethyan domain was carried out by the authors,including those in the Gulf of Mexico,eastern Brazilian continental margin,West African passive continental margin,Mid-Norway continental shelf,Northwest Shelf of Australia,South China Sea,Bay of Bengal,and the Mediterranean(Nile Delta).Forming ages,tectonic settings,and depositional environments of the main reservoirs were summarized,and the distribution patterns discussed.Results show that the main reservoirs of the deepwater oil-gas-bearing basins in the world were formed in the time of Cretaceous and Peleogene.The age of main reservoirs in the Atlantic deepwater basins show a distribution pattern of older in the north and younger in the south,whereas the main reservoirs in the Neotethyan deepwater basins are dominanted by the Peleogene.Most of the reservoirs were formed in the drifting stage.In the Atlantic deepwater basins,the main reservoirs are characterized by rifting in the north,and drifting in the south,and the main reservoirs in the Neothetyan deepwater basins were mainly formed in the drifting stage.As far as the sedimentary environment is considered,the main reservoirs in the deepwater basins are dominanted by abyssal turbidite and fluvial-deltaic sandstones.In the Atlantic deepwater basins,the distribution pattern of main reservoirs shows a trend with the littoral-neritic facies in the north,and abyssal facies in the south,while the main reservoirs in the deepwater basins in the Neotethyan domain is characterized by fluvial-delta-littoral-neritic facies.