Reflection Data Sets Research Articles

Analysis of Geologic CO2 Migration Pathways in Farnsworth Field, NW Anadarko Basin

This study reports on analyses of natural, geologic CO2 migration paths in Farnsworth Oil Field, northern Texas, where CO2 was injected into the Pennsylvanian Morrow B reservoir as part of enhanced oil recovery and carbon sequestration efforts. We interpret 2D and 3D seismic reflection datasets of the study site, which is located on the western flank of the Anadarko basin, and compare our seismic interpretations with results from a tracer study. Petroleum system models are developed to understand the petroleum system and petroleum- and CO2-migration pathways. We find no evidence of seismically resolvable faults in Farnsworth Field, but interpret a karst structure, erosional structures, and incised valleys. These interpretations are compared with results of a Morrow B well-to-well tracer study that suggests that inter-well flow is up-dip or lateral. Southeastward fluid flow is inhibited by dip direction, thinning, and draping of the Morrow B reservoir over a deeper, eroded formation. Petroleum system models predict a deep basin-ward increase in temperature and maturation of the source rocks. In the northwestern Anadarko Basin, petroleum migration was generally up-dip with local exceptions; the Morrow B sandstone was likely charged by formations both below and overlying the reservoir rock. Based on this analysis, we conclude that CO2 escape in Farnsworth Field via geologic pathways such as tectonic faults is unlikely. Abandoned or aged wellbores remain a risk for CO2 escape from the reservoir formation and deserve further monitoring and research.

Analysis of the Spatial and Temporal Changes of NDVI and Its Driving Factors in the Wei and Jing River Basins.

This study aimed to explore the long-term vegetation cover change and its driving factors in the typical watershed of the Yellow River Basin. This research was based on the Google Earth Engine (GEE), a remote sensing cloud platform, and used the Landsat surface reflectance datasets and the Pearson correlation method to analyze the vegetation conditions in the areas above Xianyang on the Wei River and above Zhangjiashan on the Jing River. Random forest and decision tree models were used to analyze the effects of various climatic factors (precipitation, temperature, soil moisture, evapotranspiration, and drought index) on NDVI (normalized difference vegetation index). Then, based on the residual analysis method, the effects of human activities on NDVI were explored. The results showed that: (1) From 1987 to 2018, the NDVI of the two watersheds showed an increasing trend; in particular, after 2008, the average increase rate of NDVI in the growing season (April to September) increased from 0.0032/a and 0.003/a in the base period (1987–2008) to 0.0172/a and 0.01/a in the measurement period (2008–2018), for the Wei and Jing basins, respectively. In addition, the NDVI significantly increased from 21.78% and 31.32% in the baseline period (1987–2008) to 83.76% and 92.40% in the measurement period (2008–2018), respectively. (2) The random forest and classification and regression tree model (CART) can assess the contribution and sensitivity of various climate factors to NDVI. Precipitation, soil moisture, and temperature were found to be the three main factors that affect the NDVI of the study area, and their contributions were 37.05%, 26.42%, and 15.72%, respectively. The changes in precipitation and soil moisture in the entire Jing River Basin and the upper and middle reaches of the Wei River above Xianyang caused significant changes in NDVI. Furthermore, changes in precipitation and temperature led to significant changes in NDVI in the lower reaches of the Wei River. (3) The impact of human activities in the Wei and Jing basins on NDVI has gradually changed from negative to positive, which is mainly due to the implementation of soil and water conservation measures. The proportions of areas with positive effects of human activities were 80.88% and 81.95%, of which the proportions of areas with significant positive effects were 11.63% and 7.76%, respectively. These are mainly distributed in the upper reaches of the Wei River and the western and eastern regions of the Jing River. These areas are the key areas where soil and water conservation measures have been implemented in recent years, and the corresponding land use has transformed from cultivated land to forest and grassland. The negative effects accounted for 1.66% and 0.10% of the area, respectively, and were mainly caused by urban expansion and coal mining.

Gas hydrate formation beneath thrust ridges: A test of concepts using 3D modelling at the southern Hikurangi Margin, New Zealand

Gas hydrates are widespread along convergent margins, but their distribution is highly variable. This variability has been attributed to a range of factors, such as the source of gas and the occurrence of permeable faults and porous or fractured reservoirs. We test these concepts on the Hikurangi Margin, where gas hydrate occurrences of variable character are well-documented by seismic reflection datasets and scientific drilling. We use 3D gas hydrate systems modelling to reconstruct processes of gas generation, migration and gas hydrate formation through time in two thrust ridges at the deformation front (Glendhu and Honeycomb ridges). We compare the results of scenarios using different fault and rock properties with indications for concentrated gas hydrates in reflection seismic data. Gas hydrate distributions are best reproduced by models predicting focussed gas migration through thrust faults and permeable strata. The gas is predominantly sourced from microbial generation beneath the gas hydrate stability zone (HSZ) in sedimentary troughs adjacent to the ridges and migrates up-dip as free gas. During progressive ridge deformation, gas generation shifts to the landward side of the ridges, where strata are rapidly buried, while erosion occurs at the crest of the ridges. A prominent back-thrust in the structurally more mature Glendhu Ridge diverts migrating gas into the HSZ and leads to preferential gas hydrate formation in the landward side of the ridge. Recycling of gas at the base of the HSZ during the past 2 Myrs led to an enrichment of gas hydrates, first in the center of the anticlines and then progressively more in the landward limbs. We propose that this process of diverting gas migration into the HSZ during thrust ridge formation is a common feature not only at the southern Hikurangi Margin, but in many convergent margins with high sedimentation rates and a thick accretionary wedge.

Urban Water Quality Assessment Based on Remote Sensing Reflectance Optical Classification

With the acceleration of urbanization, increasing water pollution means that monitoring and evaluating urban water quality are of great importance. Although highly accurate, traditional evaluation methods are time consuming, laborious, and vastly insufficient in terms of the continuity of spatiotemporal coverage. In this study, a water quality assessment method based on remote sensing reflectance optical classification and the traditional grading principle is proposed. In this method, an optical water type (OWT) library was first constructed using the measured in situ remote sensing reflectance dataset based on fuzzy clustering technology. Then, comprehensive scoring rules were established by combining OWTs and 12 water quality parameters, and water quality was graded into different urban water quality levels (UWQLs) based on the scoring results. Using the proposed method, the relative water quality of urban waterbodies was qualitatively evaluated at the macro level based on images from the multispectral imager of Sentinel-2. In addition, there was a significant positive correlation between the UWQLs and the water quality index (WQI). These results indicate the potential of this method for quantitative assessment of urban water quality, providing a new way to evaluate water quality using remote sensing algorithms in the future.

Using the Google Earth Engine to rapidly monitor impacts of geohazards on ecological quality in highly susceptible areas

Frequent geohazards have knock-on effects on ecological quality. Timely and dynamically monitoring the damage of geohazards to ecological quality is important to the geological hazards prevention, ecological restoration, and policy formulation. Existing studies mainly focused on the impacts of climate change, urbanization, and extreme weather on the ecological quality, largely ignoring the role of frequent geohazards in the highly susceptible area. At present, the impact mechanism of the high susceptibility of geohazards on ecological quality remains unknown. To fill this knowledge gap, we use the Remote Sensing Ecological Index (RSEI, a widely accepted ecological quality index) calculated on the Google Earth Engine (GEE) platform, geohazard density data, and the Landsat series of surface reflectance datasets to explore the mechanism that drives spatial–temporal variations of ecological quality. Taking the Danba County as the study area, our results indicate that the total number of geohazards is 944 during 1995–2019, and the number of geohazards fluctuates and rises every year (10 in 1995 and 82 in 2019). A conceptual framework was proposed to quantify the impact of the high susceptibility of geohazards on ecological quality by separately exploring its impact on the 4 ecological components of RSEI (i.e., greenness, wetness, dryness, and heat). We found that the density of geohazards is significantly negatively correlated with greenness (R = 0.48, Pearson Correlation Coefficient (PCC) = −0.528, p < 0.01), and humidity (R = 0.45, PCC = −0.364, p < 0.01), whereas it is significantly positively correlated with dryness (R = 0.63, PCC = -0.335, p < 0.01) and heat (R = 0.47, PCC = −0.368, p < 0.01). Therefore, geohazards make a negative contribution to ecological quality by reducing greenness and humidity and increasing dryness and heat. This study provides insights on the mechanism of geohazards on ecological quality, benefiting stakeholders in designing better management plans for sustainable ecosystem cycling, application of GEE, and geological remote sensing.

Regional Exploration and Characterisation of CO2 Storage Prospects in the Utsira-Skade Aquifer, North Viking Graben, North Sea

Subsurface CO2 storage is considered a key element of reducing anthropogenic emissions in virtually all scenarios compatible with limiting global warming to 1.5°C. The Utsira-Skade Aquifer (Utsira, Eir and Skade Formations), northern North Sea, has been identified as a suitable reservoir. Although the overall storage capacity of the full aquifer has been estimated based on regional data, it is lacking an integrated assessment of containment and internal heterogeneity, to identify optimal areas for injection and for calculation of site-specific storage capacities. A high-resolution, broadband 3D seismic reflection dataset, full waveform inverted velocity data and 102 exploration wells are utilised to provide a catalogue of CO2 storage prospects in the northern Utsira-Skade Aquifer. This is achieved through: 1) definition of the aquifer’s spatial limits; 2) calculation of porosity distribution; 3) assessment of the extent, geomorphology, thickness variability, and containment confidence (CC) of mudstones; and 4) mapping of closures through fill-to-spill simulations. CO2 storage capacity was calculated for the prospects using two approaches; using the full reservoir thickness (FRT) beneath the closures and using only the thickness from the closure top to the spill point (TSP), i.e., within structural traps. Porosity ranges from 29 to 39% across the aquifer and is higher in the Utsira and Eir Fms. relative to the underlying Skade Fm. The mudstone separating the Skade and Eir/Utsira Fm. has a thickness &amp;gt; 50 m, and is a potential barrier for CO2. Other intra-aquifer mudstones were mainly interpreted to act as baffles to flow. Structural traps at the top Utsira and Skade Fms. yield fifteen prospects, with criteria of &amp;gt; 700 m depth and FRT storage capacity of &amp;gt; 5 Mt CO2. They have a combined storage capacity of 330 Mt CO2 (FRT) or 196 Mt CO2 (TSP). Five prospects have a positive CC score (total capacity: 54 Mt CO2 FRT or 39 Mt CO2 TSP). Additional storage capacity could be achieved through more detailed analysis of the seal to upgrade the CC scores, or through use of a network of the mapped closures with a fill-to-spill approach, utilising more of the aquifer.

Cloud-Native Coastal Turbid Zone Detection Using Multi-Temporal Sentinel-2 Data on Google Earth Engine

The lack of clarity in turbid coastal waters interferes with light attenuation and hinders remotely sensed studies in aquatic ecology such as benthic habitat mapping and bathymetry estimation. Although turbid water column corrections can be applied on regions with seasonal turbidity by performing multi-temporal analysis, different approaches are needed in regions where the water is constantly turbid or only exhibits subtle turbidity variations through time. This study aims to detect these turbid zones (TZs) in optically shallow coastal waters using multi-temporal Sentinel-2 surface reflectance datasets to improve the aforementioned studies. The herein framework can be paired with other aquatic ecology remote sensing studies to establish the clear water focus area and can also be used by decision makers to identify rehabilitation areas. We selected the coastlines of Guinea-Bissau, Tunisia, and west Madagascar as our case studies which feature wide-ranging turbidity intensities across tropical, subtropical, and Mediterranean waters and applied three different methods for the TZ detection: Otsu’s method for bimodal thresholding, linear spectral unmixing, and Random Forest (RF) machine learning method on Google Earth Engine as an end-to-end process. Based on our experiments, the RF method yields good results in all study regions with overall accuracies ranging between 88 and 96% and F1-scores between 0.87 and 0.96. TZ detection is highly site-specific due to the inter-class variability that is mainly affected by the nature of the suspended materials and the environmental characteristics of the site.

Seismic features and origin of fluid escape pipes offshore Hainan Island on the northern slope of South China Sea

Fluid escape pipes form when subsurface fluids flow upwards. Various factors can lead to their occurrences. Here we present an example offshore Hainan Island in the northern South China Sea (SCS) where buried mass transport deposits (MTDs) played an important role in the formation of fluid escape pipes. Based on a three dimensional (3D) seismic reflection dataset, more than 120 seismic pipes seemed to be distributed irregularly in the shallow 230 m sequences over an area of 150 km2. The pipe field seats on a gentle slope segment that is nipped by steep and rugged slope where abundant seabed MTDs exist. The pipes can be divided into two types; ones terminate upward at the seabed with pockmarks and the others have upper extremes vanishing at levels 20–85 m below the seabed. Pipes are deduced to form due to escapes of overpressured fluid indicated by stacked high amplitude reflections (HARs) at lower part of pipes and below pipes. MTDs are observed to have a well correspondence with buried MTDs, and their couples are grouped into four relatively independent regions that are separated by normal sequences. It is suggested that these buried MTDs triggered the release of overpressured fluid due to differential compaction between MTDs bodies and overlying/lateral sediment. Buried MTDs eventually determined the spatial distribution, shape, and scale of fluid escape pipes. Selective occurrences of pipes on the gentle slope rather than the steep slope depended on the sedimentary setting, in which the undisturbed clinoform was well developed overlying widespread MTDs in late Quaternary on the gentle slope, but was absent on the steep slope. This leaded to a process of rapid deposition to favor the formation of overpressured fluid compartment at/near pipe roots on the gentle slope. Moreover, this work provided significant results for the oil company to avoid the pipeline route crossing the pipe field, even if it has a gentler terrain.

Spectral sparse recovery form a single RGB image

An efficient procedure for spectral reflectance recovery using a new compressive sensing-based spectral sparse recovery method is proposed by using the optimized sparse basis functions to recover spectral reflectance from a single RGB image. Unlike the conventional spectral recovery methods, the sparse basis functions of the proposed method are an optimal solution for obtaining the information needed to consider the characteristics of the RGB response values. The novelty of the proposed method is to obtain the optimized sparse basis functions considering the influence of the spectral reflectance dataset and the sample’s colorimetric characteristic, which meets the minimum of the spectral recovery error. Spectral and colorimetric accuracy of the proposed method is studied to verify the effectiveness compared to existing methods. As the spectral recovery results show, the proposed method is extremely effective in recovering spectral reflectance.

An Assessment of In-situ Water Quality Parameters and its variation with Landsat 8 Level 1 Surface Reflectance datasets

ABSTRACT The water quality represents the water’s physical, chemical and biological properties and depends on the environment, and anthropogenic influences. Recently, river water in Dehradun has subjected to immense pressure due to contamination from indecorous land use and urbanisation. In this study area, water quality assessment is carried out with the help of in situ observations and satellite surface reflectance from October 2018 to March 2019. Physicochemical and microbial qualities, namely, ambient temperature (AT), electrical conductivity (EC), water temperature (WT), potential hydrogen (pH), free carbon di oxide (CO2), biological oxygen demand (BOD), dissolved oxygen (DO), total dissolved solids (TDS), salinity (S), total Hardness (TH), calcium hardness (CH), magnesium hardness (MgH), sodium ion (Na), Potassium ion (K), nitrate (NO2), phosphate (PO4), and coliform concentrations (CC) were evaluated in the laboratory, plotted spatially in GIS environment and validated with the Indian Standards (IS). Furthermore, the Pearson correlation matrix was an established between the mean surface reflectance band values of Landsat-8 in the Google Earth Engine (GEE) and the water quality parameters are collected at each station location. The entire river water has been found an unsuitable for drinking but suitable for irrigation purposes. In future, such studies would be supportive for more effective management strategies to overcome the problems of water pollution.

Evidence of magmatism and rifting in the southern superior craton from the Temagami geophysical anomaly

The Temagami Geophysical Anomaly (TGA) is situated in the Paleoproterozoic Huronian Supergroup near the southern margin of Archean Superior craton, along strike from the Temagami Greenstone Belt, 50 km northeast of world-class metal endowment in the Sudbury Igneous Complex. It has been attributed to coincidental geophysical responses from Neoarchean iron formation and a Paleoproterozoic mafic–ultramafic intrusion. The TGA is investigated using integrated magnetotelluric, magnetic, gravity and seismic reflection datasets to further define the geometry of its sources; to define structures in overlying Huronian Supergroup rocks; and to examine the geometrical relationship of Archean basement structure, the Proterozoic mafic–ultramafic intrusion, and Proterozoic rift structures.Geophysical results reveal a strong conductor, interpreted to be iron formation, extending downwards from the Archean basement surface and enveloping the upper northern margin of a large magnetic, dense body at 5 km depth. The geometry of the features indicates mafic–ultramafic intrusion adjacent to greenstone rocks. Alignment of the long-axis of the intrusion with the greenstone belt suggests control on the intrusion process by the Neoarchean structures. The 60x10x10 km TGA intrusion lies within the mantle-plume, rift-related Huron-Nipissing magmatic belt and interpreted to be a member of the 2.491–2.475 Ga East Bull Lake intrusive suite. Based on this genetic relationship, the intrusion probably contributes significantly to Ni-Cu-PGE endowment of the Sudbury region. The spatial correlation of the intrusion with an overlying 20 km wide, 4.5 km deep, fault-bounded rift basin is attributed to crustal subsidence triggered by the intrusion. Seismic reflection and magnetotelluric results show younger Huronian Supergroup rocks record the transition to sedimentation on a laterally-extensive passive margin. An electrically-anisotropic, moderately-conductive layer in the Gowganda Formation is related to alteration during intrusion of the 2.200 Nipissing Diabase.

Marchenko multiple elimination and full-wavefield migration in a resonant pinch-out model

Marchenko multiple elimination schemes are able to attenuate all internal multiple reflections in acoustic reflection data. These can be implemented with and without compensation for two-way transmission effects in the resulting primary reflection data set. The methods are fully automated and run without human intervention, but they require the data to be properly sampled and preprocessed. Even when several primary reflections are invisible in the data because they are masked by overlapping multiples, such as in the resonant wedge model, all missing primary reflections are restored and recovered with the proper amplitudes. Investigating the amplitudes in the primary reflections after multiple elimination with and without compensation for transmission effects shows that transmission effects are properly accounted for in a constant-velocity model. When the layer thickness is one quarter of the wavelength at the dominant frequency of the source wavelet, the methods cease to work properly. Full-wavefield migration relies on a velocity model and runs a nonlinear inversion to obtain a reflectivity model, which results in the migration image. The primary reflections that are masked by interference with multiples in the resonant wedge model are not recovered. In this case, minimizing the data misfit function leads to the incorrect reflector model even though the data fit is optimal. This method has much lower demands on data sampling than the multiple elimination schemes, but it is prone to getting stuck in a local minimum even when the correct velocity model is available. A hybrid method that exploits the strengths of each of these methods could be worth investigating.

Investigating the potential of Sentinel-2 configuration to predict the quality of Mediterranean permanent grasslands in open woodlands

The assessment of pasture quality in permanent grasslands is essential for their conservation and management, as it can contribute to making real-time decisions for livestock management. In this study, we assessed the potential of Sentinel-2 configuration to predict forage quality in high diverse Mediterranean permanent grasslands of open woodlands. We evaluated the performance of Partial Least Squares Regression (PLS) models to predict crude protein (CP), neutral detergent fibre (NDF), acid detergent fibre (ADF) and enzyme digestibility of organic matter (EDOM) by using three different reflectance datasets: (i) laboratory measurements of reflectance of dry and ground pasture samples re-sampled to Sentinel-2 configuration (Spec-lab) (ii) field in-situ measurements of grasslands canopy reflectance resampled to Sentinel-2 configuration (Spec-field); (iii) and Bottom Of Atmosphere Sentinel-2 imagery. For the three reflectance datasets, the models to predict CP content showed moderate performance and predictive ability. Mean R2test = 0.68 were obtained using Spec-lab data, mean R2test decreased by 0.11 with Spec-field and by 0.18 when Sentinel-2 reflectance was used. Statistics for NDF showed worse predictions than those obtained for CP: predictions produced with Spec-lab showed mean R2test = 0.64 and mean RPDtest = 1.73. The mean values of R2test = 0.50 and RPDtest = 1.54 using Sentinel-2 BOA reflectance were marginally better than the values obtained with Spec-field (mean R2test = 0.48, mean RPDtest = 1.43). For ADF and EDOM, only predictions made with Spec-lab produced acceptable results. Bands from the red-edge region, especially band 5, and the SWIR regions showed the highest contribution to estimating CP and NDF. Bands 2, blue and 4, red also seem to be important. The implementation of field spectroscopy in combination with Sentinel-2 imagery proved to be feasible to produce forage quality maps and to develop larger datasets. This study contributes to increasing knowledge of the potential and applicability of Sentinel-2 to predict the quality of Mediterranean permanent grasslands in open woodlands.

Seismic illumination of small-throw seismogenic faults, Anadarko Basin, Oklahoma

Substantial increase in the occurrence of injection-induced seismicity across Central and Eastern United States in the past decade, has highlighted a need for novel approaches to geophysical subsurface imaging of potentially seismogenic faults. Active clusters of seismicity illuminate linear fault segments within the sedimentary cover and crystalline basement that were unknown until seismicity began. Such surprises are due to the limited availability of 3D seismic reflection surveys and the difficulty of imaging relatively shallow earthquake events from sparse seismic monitoring arrays. The Sooner Trend Anadarko Basin Canadian Kingfisher Counties (STACK) play of the Anadarko Basin, Oklahoma, provides an opportunity to investigate these earthquake-prone basement faults. Modern high-quality seismic data acquired to map unconventional resource plays in the STACK enable us to assess the detailed subsurface structure. Furthermore, because of increased earthquake risk from anthropogenic activities in the past decade, state regulatory agencies have deployed a dense array of seismic monitoring stations, which allows us to integrate earthquake data with seismic reflection data for analysis of active faulting. We have mapped structural deformation using a suite of seismic attributes, including multispectral coherence, volumetric curvature, and aberrancy, in a 3D seismic reflection data set covering 625 sq mi of the STACK area. To unravel the relationship between the structures and seismicity, we use relocated locally recorded earthquakes and compute the focal mechanism solution for the events. Our results reveal previously unmapped small-throw (&lt;120 m) fault segments with dominant north–south, northwest, and northeast trends, most of which extend from the basement up into the shallower sedimentary Hunton and Woodford Formations. Because of the small offset, we find that aberrancy and the curvature attribute best illuminate the basement-rooted faults in the sedimentary cover. Fault segments with significant vertical offset are better illuminated by band-limited multispectral coherence. We argue that the inherited structure of these faults makes them mostly illuminable by flexure-related seismic attributes, especially within the sedimentary cover. The integration of the illuminated faults with relocated earthquakes and focal mechanism solutions shows that the illuminated faults that have hosted intrasedimentary and/or basement seismicity are reactivated by strike-slip faulting. We hypothesize that careful attribute mapping of faults and related flexures, integrated with recent seismic activity data, and an understanding of the local stress and geomechanical properties, can help mitigate seismic hazards in similar intraplate geological settings where small-throw faults predominate.

Evaluating the segmented post-rift stratigraphic architecture of the Guyanas continental margin

Segmentation of the Guyanas continental margin of South America is inherited from the dual-phase Mesozoic rifting history controlling the first-order post-rift sedimentary architecture. The margin is divided into two segments by a transform marginal plateau (TMP), the Demerara Rise, into the Central and Equatorial Atlantic domains. This paper investigates the heterogeneities in the post-rift sedimentary systems at a mega-regional scale (&gt;1000 km). Re-sampling seven key exploration wells and scientific boreholes provides new data (189 analysed samples) that have been used to build a high-resolution stratigraphic framework using multiple biostratigraphic techniques integrated with organic geochemistry to refine the timing of 10 key stratigraphic surfaces and three megasequences. The results have been used to calibrate the interpretation of a margin-scale two-dimensional seismic reflection dataset, and to build megasequence isochore maps, structural restorations and gross depositional environment maps at key time intervals of the margin evolution. Our findings revise the dating of the basal succession drilled by the A2-1 well, indicating that the oldest post-rift sequence penetrated along the margin is late Tithonian age (previously Callovian). Early Central Atlantic carbonate platform sediments passively infilled subcircular-shaped basement topography controlled by the underlying basement structure of thinned continental crust. Barremian–Aptian rifting in the Equatorial Atlantic, caused folding and thrusting of the Demerara Rise, resulting in major uplift, gravitational margin collapse, transpressional structures and peneplanation of up to 1 km of sediment capped by the regional angular Base Albian Unconformity. Equatorial Atlantic rifting led to margin segmentation and the formation of the TMP, where two major unconformities developed during the intra Late Albian and base Cenomanian. These two unconformities are time synchronous with oceanic crust accretion offshore French Guiana and in the Demerara–Guinea transform, respectively. A marine connection between the Central and Equatorial Atlantic is demonstrated by middle Late Albian times, coinciding with deposition of the organic-rich source rock of the Canje Formation (average total organic carbon 4.21%). The succession is variably truncated by the Middle Campanian Unconformity. Refining the stratigraphic framework within the context of the structural evolution and segmentation of the Guyanas margin impacts the understanding of key petroleum system elements. Supplementary material : Photographs of sandstone petrography thin sections (Fig. S1); calcareous nannofossil plates (Fig. S2); palynology reports for A2-1 and FG2-1 (Fig. S3); taxonomy description of new species; sample table and organic geochemistry results (Table S1); and nannofossil distribution charts (Table S2) are available at https://doi.org/10.6084/m9.figshare.c.5280490

Integration of gravity, magnetic, and seismic data for subsalt modeling in the Northern Red Sea

Rifts and rifted passive margins are often associated with thick evaporite layers, which challenge seismic reflection imaging in the subsalt domain. This makes understanding the basin evolution and crustal architecture difficult. An integrative, multidisciplinary workflow has been developed using the exploration well, gravity and magnetics data, together with seismic reflection and refraction data sets to build a comprehensive 3D subsurface model of the Egyptian Red Sea. Using a 2D iterative workflow first, we have constructed cross sections using the available well penetrations and seismic refraction data as preliminary constraints. The 2D forward model uses regional gravity and magnetic data to investigate the regional crustal structure. The final models are refined using enhanced gravity and magnetic data and geologic interpretations. This process reduces uncertainties in basement interpretation and magmatic body identification. Euler depth estimates are used to point out the edges of high-susceptibility bodies. We achieved further refinement by initiating a 3D gravity inversion. The resultant 3D gravity model increases precision in crustal geometries and lateral density variations within the crust and the presalt sediments. Along the Egyptian margin, where data inputs are more robust, basement lows are observed and interpreted as basins. Basement lows correspond with thin crust ([Formula: see text]), indicating that the evolution of these basins is closely related to the thinning or necking process. In fact, the Egyptian Northern Red Sea is typified by dramatic crustal thinning or necking that is occurring over very short distances of approximately 30 km, very proximal to the present-day coastline. The integrated 2D and 3D modeling reveals the presence of high-density magnetic bodies that are located along the margin. The location of the present-day Zabargad transform fault zone is very well delineated in the computed crustal thickness maps, suggesting that it is associated with thin crust and shallow mantle.

On the negative polarization's effects at top of atmosphere

Polarized signal has been proven to be sensitive to the aerosol optical depth and aerosol microphysical parameters. However, in most current applications, the directions of polarization, which are expressed by the sign of polarization, have long been regarded as minor factor. In most remote sensing retrievals, the absolute values of negative polarizations are considered. Therefore, whether this neglection will introduce uncertainty in remote sensing has not been investigated. In this study, TOA polarized reflectances are calculated with the measured surface (with sign) and modeled (without sign) polarized reflectance to obtain the TOA polarized reflectance dataset. Our results suggest that 7% of the surface measured polarized reflectance is negative, while after the vector radiative transfer calculation, this proportion increases to 20–50%. Although correlations between absolute values of measured and modeled data are high (>0.99), when including the effects of the sign, the correlations will decrease to less than 0.5 or even 0.2, and RMSE will increase 10 times. These discrepancies will introduce a lot of uncertainty in polarized remote sensing retrieval when mixed pixels with opposite polarizations for subpixels occur. Furthermore, the same polarization for different objects is another problem when there are both negative and positive polarizations. Our study is particularly important for future applications of polarized signals to obtain accurate and reliable results.

Automated Global Shallow Water Bathymetry Mapping Using Google Earth Engine

Global shallow water bathymetry maps offer critical information to inform activities such as scientific research, environment protection, and marine transportation. Methods that employ satellite-based bathymetric modeling provide an alternative to conventional shipborne measurements, offering high spatial resolution combined with extensive coverage. We developed an automated bathymetry mapping approach based on the Sentinel-2 surface reflectance dataset in Google Earth Engine. We created a new method for generating a clean-water mosaic and a tailored automatic bathymetric estimation algorithm. We then evaluated the performance of the models at six globally diverse sites (Heron Island, Australia; West Coast of Hawaiʻi Island, Hawaiʻi; Saona Island, Dominican Republic; Punta Cana, Dominican Republic; St. Croix, United States Virgin Islands; and The Grenadines) using 113,520 field bathymetry sampling points. Our approach derived accurate bathymetry maps in shallow waters, with Root Mean Square Error (RMSE) values ranging from 1.2 to 1.9 m. This automatic, efficient, and robust method was applied to map shallow water bathymetry at the global scale, especially in areas which have high biodiversity (i.e., coral reefs).

Evaluating plant photosynthetic traits via absorption coefficient in the photosynthetically active radiation region

Absorption of radiation in the photosynthetically active radiation (PAR) region is significantly influenced by plant biochemistry, structural properties, and photosynthetic pathway. To understand and quantify the effects of these traits on absorbed PAR it is necessary to develop practical and reliable tools that are sensitive to these traits. Using a semi-analytical modeling framework for deriving the absorption coefficient of plant canopies from reflectance spectra, we quantify the effects of functional, structural and biochemical traits of vegetation on the relationship between the absorption coefficient in the PAR region (αpar) with canopy characteristics such as the fraction of PAR absorbed by photosynthetically active vegetation (fAPARgreen) and chlorophyll (Chl) content. The reflectance dataset used in the study included simulated data obtained from a canopy reflectance model (PROSAIL) and empirical data on three diverse crop species with different leaf structures, canopy architectures and photosynthetic pathways (rice, maize and soybean) acquired at proximal (i.e., using field spectroradiometers) and remote (i.e., Landsat TM and ETM+) distances. Results show the usefulness of αpar derived from reflectance data for assessing not only the photosynthetic status of vegetation, but also the effects of different functional, structural and biochemical traits on plant performance. Furthermore, these assessments can be made using data acquired by satellite sensor systems such as the Landsat series, which are available since the 1980s, thus facilitating the analysis of the photosynthetic status of terrestrial ecosystems throughout the world with a high temporal depth.

Improvement of chlorophyll content estimation on maize leaf by vein removal in hyperspectral image

Leaf chlorophyll content (LCC) is one of nutritional parameters which could be estimated by Hyperspectral image (HSI) technology by combining spatial and spectral information. The objective of this study was to propose a novel segmentation algorithm to remove the influences of the veins in maize leaves so as to improve the accuracy of LCC modeling. Firstly, an enhanced green peak feature (EGPF) was built by local extremum points at 451, 552 and 648 nm, and then the image of EGPF was automatically segmented by OTSU method to get region of interest (ROI) of all leaf regions (ROI-ALR) without background and main stem. Secondly, an enhanced red valley feature (ERVF) was proposed to enlarge the edge difference between veins and mesophylls. ROI of only mesophyll regions (ROI-OMR) were extracted by removing of leaf veins resorted to edge segmentation. For the two spectral reflectance datasets from ROI-ALR and ROI-OMR, multiplicative scattering correction (MSC) was implemented. Correlation analysis (CA) and Random-Frog (RF) coupled with partial least square regression (PLSR) were applied to select characteristic wavelengths and establish LCC estimating models. Compared ROI-ALR- CA-PLSR with ROI-OMR-CA-PLSR, Rv2 increased from 0.43 to 0.52 and RMSE decreased from 4.11 to 3.61; Compared ROI-ALR- RF -PLSR with ROI-OMR- RF –PLSR, Rv2 increased from 0.83 to 0.86 and RMSE decreased from 2.14 to 1.86. The proposed HSI segmentation method for veins removal provides an effective strategy to improve LCC diagnosis of maize leaves.