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Analysis of SRTM data as an aid to hydrocarbon exploration in a frontier area of the Amazonas Sedimentary Basin, northern Brazil
Marine and Petroleum Geology 73 (2016) 528e538
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Marine and Petroleum Geology journal homepage: www.elsevier.com/locate/marpetgeo
Research paper
Analysis of SRTM data as an aid to hydrocarbon exploration in a frontier area of the Amazonas Sedimentary Basin, northern Brazil Delano M. Ibanez a, *, Raimundo Almeida-Filho b, Fernando P. Miranda a a b
cio Macedo, 950, Cidade Universita ria, Ilha do Funda ~o, Rio de Janeiro, Brazil Petrobras Research and Development Center (CENPES), Av. Hora ~o Jos National Institute for Space Research-INPE, C. P. 515, Sa e dos Campos, Brazil
a r t i c l e i n f o
a b s t r a c t
Article history: Received 9 September 2014 Received in revised form 11 December 2015 Accepted 23 March 2016 Available online 28 March 2016
The Shuttle Radar Topography Mission (SRTM) provided an unprecedented source of space-borne topographic information that has shown to be of particular interest for studies in densely vegetated tropical areas, such as Central Amazonia. The digital elevation models produced in that region show subtle details of the terrain that usually appear blurred in conventional remote sensing images. Interpretation of an SRTM-derived drainage network and geomorphometric features revealed several drainage anomalies, which are possibly the surface expression of buried morphostructural features. Integration with geological and geophysical ancillary data strongly suggested that interpreted features constitute potential structural sites for hydrocarbon exploration. However, due to their inferred nature, the structures herein identified are not by themselves a justification for drilling. However, they do provide information for planning seismic surveys, thus reducing costs of the exploration campaigns, as well as minimizing potential environmental impacts of such an enterprise in areas of tropical rain forests. Despite the relatively small size of the study area, it is expected that procedures presented in this paper can be successfully applied throughout the approximately 1,000,000 km2 of sedimentary basins in the Brazilian Amazonian region. © 2016 Elsevier Ltd. All rights reserved.
Keywords: Morphostructural analysis Petroleum exploration SRTM DEM Amazonas basin
1. Introduction Remote sensing technology is nowadays a well-accepted auxiliary tool for hydrocarbon exploration in frontier areas, since it may provide relevant information for planning seismic surveys, thus reducing costs of the exploration campaigns (e.g. Mello et al., 1996; Mitra, 2011), and minimizing potential environmental impacts of such an enterprise. The use of this technology in low-relief sedimentary basins aims at identifying subtle surface expressions of buried structural features that may constitute possible prospecting sites. The term low-relief basin refers here to a sedimentary area, whose stratigraphic and structural features are completely buried by mostly undeformed younger sedimentary units and soils, in addition to the vegetation cover. Under such physiographical conditions, surface expressions of buried structures may be denoted by the local organization of drainage network. The expected arrangement in low relief basins
* Corresponding author. E-mail addresses: [email protected] (D.M. Ibanez), [email protected] (R. Almeida-Filho), [email protected] (F.P. Miranda). http://dx.doi.org/10.1016/j.marpetgeo.2016.03.024 0264-8172/© 2016 Elsevier Ltd. All rights reserved.
filled with a flat-lying sedimentary section is the dendritic pattern, characterized by irregular drainage branching, with tributaries joining main streams at different angles (Howard, 1967). However, as recognized by many authors in diverse climatic and surface conditions (e.g. Howard, 1965; Miranda and Boa Hora, 1986; Deffontaines and Chorowicz, 1991; Berger, 1994; Raymond et al., 1994; Chauvaud and Delfaud, 2002; Araújo et al., 2005; Ollarves et al., 2006; Almeida-Filho et al., 2010; Burrato et al., 2012; Terrizzano et al., 2014), drainage analysis may indicate the presence of buried geological features, which are suggested by specific anomalous patterns relative to the regional network. Therefore, stream alignment, or rectilinear stream segments, may be interpreted as the surface expression of buried faults and fractures. Furthermore, radial and annular drainage patterns, or a combination of them, are of special interest, since they may be associated with subtle surface expressions of buried domal structures that constitute potential hydrocarbon structural traps. The studied area is situated in Central Amazonia, which is unique in terms of general lack of outcrops, extensive rain forest and cloud cover, as well as a generally flat topography. Thus, the application of traditional geomorphological mapping is time
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consuming and costly activity. Moreover, the resolution of available geomorphological mapping (i.e., 1:1,800,000 e IBGE, 2010) does not allow reliable attribution of landforms in a particular hydrographic basin, but at the Amazonas Basin scale only. Therefore, the geomorphological mapping of this region requires semi-automated methods for the identification and classification of terrain features. These landforms can be derived using the SRTM DEM by means of a semi-automated unsupervised method, such as fuzzy k-means clustering approach (e.g. Seijmonsbergen et al., 2011). Thus, in this article, we analyze the drainage network and geomorphometric features extracted from an SRTM digital elevation model, supported by ancillary geological and geophysical information, aiming to identify structures that may constitute potential hydrocarbon prospects in a test-site of the Amazonas Sedimentary Basin, located approximately 100 km east of the city of Manaus (Fig. 1). Such an approach is considered an effective lowcost method for early stages of exploration in the Amazonas Sedimentary Basin, where discoveries have been hindered by a limited availability of seismic data and drilling, as well as by logistical and environmental restrictions imposed by the tropical rain forest.
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Presently there are only two commercial natural gas accumulations in this basin. Nevertheless, the perspectives of new discoveries is good, since the all essential elements of a petroleum system (as defined by Magoon and Dow, 1994) are present in the region (Gonzaga et al., 2000). 2. Geological setting Completely covered by the tropical rain forest of northern Brazil, the Amazonas Sedimentary Basin is about 1300 km long and 350 km wide. The Amazonas River flows approximately along the main central trough of the basin, dividing it into northern and southern flanks. The Amazonas Basin is separated from the Sol~es Basin to the west by the Purus Arch, and from the Marajo imo Arch (Fig. 1a). Igneous and metaBasin to the east by the Gurupa shields morphic Precambrian rocks of the Guiana and Guapore bound the basin to the north and south, respectively (Gonzaga et al., 2000). In the Amazonas Basin, a pile of Paleozoic sediments about 5500 m thick is organized into four sequences, separated by regional unconformities and overlaid by Upper-Cretaceous to
Fig. 1. Location of the study area. (a) Stratigraphic units and tectonic features of northern Brazil (after Schobbenhaus et al., 2004). (b) Detailed view of the study area, showing the main rivers and (A) Azul~ ao and (B) Japiim gas fields, as depicted using the SRTM DEM. Manaus is the capital of the Amazonas State, northern Brazil.
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Fig. 2. Aerial view of the tropical rain forest and of a stream in the Amazonas Basin. The vegetation cover is a hindrance to the application of more classical geomorphological methods.
Quaternary clastic continental deposits (Cunha et al., 2007; Caputo, 2011). Marine shales, sandstones and diamictites of the Trombetas Group constitute the Upper Ordovician-Lower Devonian sequence. In addition, sandstones, siltstones, and shales of the Urupadi and groups represent the Middle Devonian-Lower Carboniferous Curua sequence. The Faro Formation alone is the Middle Carboniferous sequence, which is characterized by fluvial-deltaic sandstones and mudstones with influence and coastal storms. Furthermore, clastic s Group constitute the Middle and chemical rocks of the Tapajo Carboniferous-Permian sequence. The tectonic framework of the Amazonas Basin comprises hinge lines, half-grabens, platforms, and accommodation zones that promote polarity inversion. The Amazonas Basin has a well-developed petroleum system, in which Upper Devonian hydrocarbon source rocks of the Barreirinha Formation up to 150 m thick are widely distributed, with average TOC of 4%, and peak of 10% (Gonzaga et al., 2000). The main reservoir rocks are Carboniferous eolian sandstones of the Monte Alegre Formation and Neocarboniferous sandy basal layers of the
Fig. 3. Conventional SAR image of the study area obtained by the JERS-1 satellite (a), and the corresponding SRTM digital elevation model (b) highlighting details of the drainage network.
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Nova Olinda Formation. Evaporites of the Nova Olinda Formation ~o are the top seals for gas accumulation in sandy layers of the Azula and Japiim fields (Fig. 1b). In addition, carbonates of the Carboniferous Itaituba Formation constitute in the seal for the underlying sandstones of the Monte Alegre Formation (Milani and Zalan, 1999). An Early Jurassic magmatism represented by sills and dikes of basic rocks contributed to the thermal maturity of the source rocks, while tectonic event (Early Jurassic-Early Cretaceous) was the Jurua responsible for the development of compressional structural traps, which are constituted by. asymmetric anticlines in the upthrown blocks of the reverse faults. Traps also occur in asymmetric anticlines on top of upthrown blocks of normal faults developed during the Paleozoic. Stratigraphic traps can also be present where sands pinch out into evaporites. (Neves, 1990; Gonzaga et al., 2000). Seismic data indicate that these structural traps do not deform the deposits of Cretaceous to Quaternary age about 300 m thick (Costa, 2002). The study site is located in the northern flank of the Amazonas Basin, encompassing a surface of approximately 110 km by 70 km that is entirely covered by undisturbed tropical rain forest. The relief consists predominantly of extensive low plateaus differently dissected, but flood plains, fluvial terraces, sandy plains, tabular and hilly surfaces are also observed (Ibanez et al., 2014a). The elevation range is about 150 m between the large floodplains of the Amazonas and Uatum~ a rivers, and the main drainage divides. Geologically, the investigated area is largely occupied by Cenozoic ~o Formation (Fig. 1a), which is made up of rocks of the Alter do Cha quartz arenites coarse to medium grained, locally conglomeratic (Costa, 2002; Caputo, 2011). It is also worth noting that throughout the region's main rivers, there are Quaternary deposits formed by clay and the alluvial plains of sand-rich sediments deposited in the floodplains, levees and abandoned channels (Latrubesse and Franzinelli, 2002). 3. Material and methods 3.1. SRTM data In tropical rain forest regions, radar backscatter at C-band (5.6 cm) results from multiple interactions of the incident wave with components of the vegetation canopy (trunks, branches, twigs, and leaves). Thus, the digital elevation models produced by the SRTM in such areas do not express direct information from the terrain itself, but from the vegetation canopy within the approximately 92 m spatial resolution element of the system (Rabus et al., 2003). Topography is enhanced because the mean height of the tree
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crowns follows the ground surface on a regional scale. Consequently, the resulting digital elevation model reproduces the terrain morphology. In this process, the drainage network is emphasized due to differences in heights between uncovered river surface and the adjacent forest (Fig. 2). The SRTM DEM should nevertheless be used carefully in heavily vegetated areas because there is a positive relationship between elevation error and height of the canopy (Hofton et al., 2006). In this regions, radar waves in the C-band will scatter and deflect upward again, from near the top of the canopy e from 0.5 to 0.75 of the height of the trees (Reuter et al., 2009). Although a DEM derived from topographic maps based on a field survey in heavily vegetated areas that are scarce in the Amazon region will be much more reliable than those derived from radar, an SRTM DEM, on the other hand, always shows much more local detail (such as micro- and meso-relief) (Reuter et al., 2009). Furthermore, SRTM digital elevation models have opened up unprecedented opportunities for studies in densely vegetated tropical areas, because they enhance subtle details of the terrain that are costmarily blurred in conventional remote sensing images (Almeida-Filho and Miranda, 2007). For comparison purposes, Fig. 3 shows the study area through a conventional L-band synthetic aperture radar (SAR) image obtained by the Japanese Earth Resources Satellite-1 (JERS-1), and the corresponding SRTM digital elevation model. Intermediate gray levels in the JERS-1 image represent the intensity of the radar return from the components of the forest canopy (trunks branches, twigs and leaves) with some contribution from the rough ground surface. Light gray levels result from radar double-bounce effect in areas of flooded forests along drainages, and black is associated with free water surfaces that are smooth. In the SRTM digital elevation model, gray levels vary accordingly from darker to lighter shades as the terrain topography increases. Therefore, the value range of the color scale of the SRTM data can be easily adjusted to further emphasize the desired topography features, which is impossible with the radar dataset. The drainage network was automatically extracted from the SRTM digital elevation model using the D8 algorithm presented by Jenson and Domingue (1988) and available in the DWCON tool from PCI software package, version 10.0. Such an approach allows the extraction of a drainage network in raster format. Taking first-order rivers as a reference, the drainage network was geometrically corrected, using a cartographic base provided by the Brazilian Institute of Geography and Statistics (IBGE). In the following step, the drainage network was converted to the vector format using the RTV tool from PCI 10.0 (Greenlee, 1987). This result was then incorporated to a geocoded dataset that included previous geological and
Fig. 4. Surface expression models of drainage arrangements for obscured and buried morphostructural features at initial (a), intermediate (b), and advanced (c) stages of erosion (after Berger, 1994), corresponding, respectively, to the examples identified in the study area: Madruba (d), Aneba (e) and Bacabudo II (f). See Fig. 6b for location.
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~ River region: a) elevation; b) TWI; c) VDepth; d) MRVBF; e) DFM; f) PERC; g) CONI; Fig. 5. A preview of the Land Surface Parameters (LSPs) derived using SRTM DEM for the Uatuma h) OPENNESS. See Fig. 1 for location.
geophysical data available in the study area (faults, drilled wells, and the Bouguer gravity map). 3.2. Drainage anomalies The Paleozoic stratigraphic intervals of exploratory interest in the Amazonas Basin are covered by younger, mostly undeformed Cretaceous to Quaternary sediments. Thus, the analysis of the drainage network aiming at the identification of buried structural features is based on the premise that the present-day landscape may reflect features inherited from the past. Such features would be expressed by subtle arrangements of the drainage network, which would adjust their channel to surface conditions controlled by buried structural features (e.g. Miranda and Boa Hora, 1986). The mechanisms by which subsurface structural features become apparent in recent sediments are not fully understood. It is believed (e.g. Berger, 1994 and references therein) that differences in the type and thickness of sediment in the vicinity of the buried structure can result in differential vertical stresses, which may cause partial reactivation of structures and lead to local increases in topographic relief or increased fracture density at the surface. Lateral variations in the sedimentary column covering buried structures may result in differential compaction and subsidence and thus also lead to local changes in topographic relief or surface fracturing (Rumsey, 1971; Berger, 1994; Holbrook and Schumm, 1999). According to Berger (1994), the geomorphic evolution of a domal feature can be categorized into three erosive stages (Fig. 4): (a) initial, (b) intermediate, and (c) advanced. The initial dissecting of a domal structure is controlled by radial consequent drainages1 that flow to subsequent rivers,2 partially adjusted to the edges of the structure. The intermediate stage of erosion is characterized by the development of a central stream originated from an obsequent drainage3 that evolves through the capture of the consequent radial
1 Consequent is drainage whose course or direction is dependent on or controlled by the general form or slope of the land surface in the dip direction. 2 Subsequent is drainage that has developed its valley adjusted to the regional structure, flowing approximately in the direction of the strike of the underlying strata. 3 Obsequent is drainage that flows in a direction opposite to that of an original consequent drainage, or in a direction opposite to that of the dip of the local strata.
drainages. The advanced stage of erosion results in substantial lowering of the structure, and in the development of a central stream splitting the obscured structural feature, which is now partially suggested by segments of subsequent drainages. Besides illustrating these three models of geomorphic evolution of domal structures, Fig. 4 shows actual examples of correspondent drainage anomalies identified in the study area through the visual analysis of the hydrographic network extracted from SRTM DEM. Taking into account the methodological approach and reasoning discussed above, several drainage anomalies were identified in the study area. The possible geological meaning and potential prospecting significance of these features will be discussed in the sections 4 and 5. 3.3. Semi-automated identification and extraction of geomorphological features Geomorphometry is an interdisciplinary science that combines earth science, mathematics and computation to describe the earth's surface as a numerical representation with quantitative descriptors (Pike, 1995, 2000; Rasemann et al., 2004). The fundamental operation in geomorphometry is the extraction and classification of parameters and objects from digital elevation models (Pike et al., 2009). In this context, geomorphological maps created through photo-interpretation and field observation are gradually being replaced by geomorphological maps that are extracted from DEMs (Seijmonsbergen et al., 2011). In this study, geomorphological classes were optimally extracted using the fuzzy k-means clustering approach as employed by Burrough et al. (2000) and Seijmonsbergen et al. (2011). Firstly, this approach involved the selection of land surface parameters (LSPs) derived from the SRTM DEM in order to explain the distribution of geomorphological classes. The LSPs selected were: elevation, topographic wetness index (TWI), valley depth (VDEPTH), multiresolution valley bottom flatness index (MRVBF), difference from the topographic mean (DFM), residual percentage index of the elevation (PERC), convergence index (CONI) and topographic openness with radii of 250 m (Fig. 5aeh, respectively). These parameters were chosen because they highlight subtle changes in morphology and roughness of regions characterized by low relief (Seijmonsbergen et al., 2011), such as the study area. The LSPs were extracted using the SAGA GIS software (Hengl, 2007).
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The next step was to convert the LSPs into independent components using principal component analysis (PCs). Thus, the 8 original LPSs were converted to 8 PCs in order to reduce potential error introduced through multicollinearity of predictor variables (Hengl, 2007). Therefore, geomorphological classes were extracted of the 8PCs using the fuzzy k-means classification. This unsupervised approach will optimally assign each individual pixel to an abstract class; the class centers were selected in such way that the sum of squares within groups is minimized (Bezdek et al., 1984; Burrough and McDonnell, 1998). After this step, classes editing
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and aggregation were interactively performed to correct possible confusion and misclassification. Finally, in order to improve accuracy and aesthetics, a mode filter 7 7 was applied to the geomorphological classification. The mode filter computes the mode of the gray-level values inside the filter window surrounding each pixel. Mode filtering was utilized for removing small, extraneous islands of data by replacing them with values corresponding to their surroundings, thus eliminating “speckles” (Teodoro et al., 2009).
Fig. 6. Drainage network automatically extracted from the SRTM digital elevation model (a) and identified drainage anomalies (b).
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4. Results 4.1. Drainage anomalies In the Fig. 6a, the study area presents, in general, dendritic to sub-dendritic drainage patterns, with tributaries joining main streams at different angles. However, radial/annular drainage patterns can be identified locally, which may be associated with
buried domal features. In order to avoid any bias, drainage analysis was performed without consulting the geological or geophysical information available in the study area. From this analysis, fourteen drainage anomalies were identified and named after the main stream they are associated with. Stream arrangements that configure these anomalous patterns vary considerably in extension, from about 4 km up to 20 km in diameter (Fig. 6b). Anomalous drainage patterns identified in the study area can be grouped
Fig. 7. Anomalous drainage patterns compared with the results of (a) available geomorphological map of study area (IBGE, 2010) and, (b) the semi-automated unsupervised geomorphological classification, main regional geological features (Neves, 1990), gas fields and wells. Drainage anomalies in the western part correspond mainly to the hilly surface, ~o and (B) Japiim gas fields. whilst the anomalies in the southeastern portion are related to floodplains and mostly sandy plains. Letters indicate the (A) Azula
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Fig. 8. Anomalous drainage patterns compared with the geological map (Schobbenhaus et al., 2004), main regional geological features (Neves, 1990), gas fields and wells. The ~o and (B) Japiim gas fields. drainage anomalies are located on Cenozoic rocks of the Alter do Ch~ao Formation. Letters indicate the (A) Azula
into two main sets. The first one comprises features situated in the western part of the study site, represented by the Tucunarezinho, , Bom Jesus-I, Bom Jesus-II, Bacabudo-I, and Bacabudo-II Aneba drainage anomalies. The other set includes the Maquarazinho, , and Madrub Sanabani-Itabani, Caiaue a drainage anomalies that are located in the southeastern part of the investigated region.
4.2. Geomorphological map The final geomorphological map is shown in Fig. 7. This product is based on the unsupervised classification implemented in the investigated region, which allowed defining 3 kinds of landforms based on 8 LSPs: floodplains, sandy plains and hilly surfaces. Floodplains represent a set of aggradation forms produced by
Fig. 9. Anomalous drainage patterns compared with the Bouguer gravity map and main regional geological features (Neves, 1990). The set of drainage anomalies to west is located along the northern border of a region with low gravity values, which is bounded by a normal fault.
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modern river sedimentation, consisting of seasonally flooded areas that fill the valleys of the main channels. Sandy plains constitute flat surfaces developed above an extremely sandy substrate and are found around valley bottoms and interfluves. Hilly surfaces bring together a set of landforms that are characterized by more intense morphodynamic activity and by a distinctly marked dissection (Ibanez et al., 2014a). These results demonstrate that the Uatum~ a River landscape is more compartmentalized than shown in the available geomorphological map (compare Fig. 7a and b). 5. Discussions Drainage anomalies were compared with ancillary geological and geophysical information with the aim of investigating whether they could be associated with possible buried structural features, or would merely represent surface arrangements without any apparent structural control. They were only observed in Cenozoic ~o Formation (Fig. 8). However, the absence rocks of the Alter do Cha of anomalous features in the north and northeastern portions of the study area may be a consequence of geomorphological dynamics, and not simply an aspect of lithology. These portions mainly correspond to floodplains (Fig. 7). Floodplains are represented by flat surfaces and modern river sedimentation; they thereby can continuously obscure possible traces of domal structures, thus hindering the identification of drainage anomalies associated with these features. Conversely, drainage anomalies in the western and southeastern parts of the investigated site mainly correspond to hilly surface and sandy plains, respectively (Fig. 7). These landforms therefore enhance the surface expression of geological structures. The combination of the Bouguer gravity anomaly map with previously mapped structures and the identified drainage anomalies is shown in Fig. 9. The main feature highlighted in the Bouguer map is a region with low gravity values in the central part of the
studied area, whose northern border is defined by a prominent normal fault mapped by Neves (1990). This NEeSW structural feature that dips southeastward coincides with the boundary of the low-gravity, thus reinforcing the interpretation of a half-graben. The hinge line on the northern flank of the Amazonas Basin dips to the southeast (Gonzaga et al., 2000) and crosses diagonally the southeastern part of the study area, running roughly parallel to the above mentioned normal fault. In this region, seismic data indicated the existence of a set of reverse faults associated with the tectonic event at the top of the Carboniferous seal rocks Jurua (Fig. 10a), which follow the main direction of the hinge line, with upthrown blocks to the southeast (Miranda et al., 1994). Comparison of the two distinct sets of drainage anomalies with the geological information shown in Figs. 7e9 strongly suggests that these features are controlled either by the normal fault defining the northern edge of the gravity low or by the normal fault located along the hinge line. On one hand, the drainage anomalies , Bom Jesus-I, Bom Jesus-II, Bacanamed as Tucunarezinho, Aneba budo-I, and Bacabudo-II constitute a trend of morphostructural features striking NEeSW in the upthrown block of the normal fault. , and On the other hand, Maquarazinho, Sanabani-Itabani, Caiaue drainage anomalies are spatially associated with the Madruba Lucas Borges lineament, with the northern hinge line of the Amazon Basin (Figs. 7e9) and with the reverse faults situated in the southeastern part of the study area (Fig. 10a). With the aim of evaluating the prospective significance of the identified drainage anomalies, we also investigated whether the ~o and Japiim gas fields are located coincidentally with one of Azula ~o gas field, the drainage anomalies (Figs. 7 and 8). The Azula discovered in 1999, comprises a 12 m thick reservoir at a depth of 1650 m. Tests revealed a production potential of 700,000 m3/day, plus a small percentage of condensate (ANP, 2008). Throughout this gas field, a NE-oriented seismic line published by Dignart and Vieira
Fig. 10. a) Drainage anomalies superimposed on the two-way travel time structural map at the top of the Itaituba Formation. Contour interval is 20 ms (modified from Miranda et al., 1994). Drainage anomalies are located along several reverse faults and one anticlinal. b) Selected portion of a NEeSW seismic line (0254-0151 line) that includes well 1-RUT-1AM and illustrates gently folded layers of Paleozoic rocks (modified from Dignart and Vieira, 2009). c) Two-way travel time structural map at the top of the Nova Olinda Formation. Contour interval is 25 ms (modified from Dignart and Vieira, 2009).
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6. Conclusions Analysis of the SRTM-derived drainage network suggested the presence of buried geological structures in a study area of the Amazonas Sedimentary Basin, which encompasses the Uatum~ a River. Combination of a semi-automated unsupervised geomorphological classification of the SRTM data and previous geological information indicates that the identified morphostructural features may constitute hydrocarbon prospective sites. However, because they are defined based solely on geomorphologic inference, the structures herein suggested are not themselves justification for drilling. Conversely, they provide information for planning seismic surveys, thus reducing costs of the exploration campaigns, as well as minimizing the potential environmental impacts of such enterprises in areas of tropical rain forests. The spatial coincidence be drainage anomaly and Azula ~o gas field shows tween the Madruba that procedures discussed in this paper can be successfully applied elsewhere in the Brazilian Amazonia, as well as in other sedimentary basins of the world. Acknowledgments SRTM data were downloaded from the USGS/EROS Data Center (http://eros.usgs.gov/srtm). The JERS-1 SAR image was acquired as part of the Global Rain Forest Mapping Project (GRFM) led by the Earth Observation Research and Application Center (EORC) of the Japan Aerospace Exploration Agency (JAXA). Two anonymous reviewers are appreciated for their helpful comments and suggestions to improve the quality of this paper. References
Fig. 11. a) Ring fence of the Azul~ao gas field (black line) superimposed on the Madruba drainage anomaly (white line - see location in Fig. 6) and well 1-RUT-1-AM. The background corresponds to a shaded relief map derived from the SRTM data. b) Topographic profile along the transect A-B (Fig. 11a). The discovery well 1-RUT-1-AM is located exactly at the center of the morphostrutural feature, attesting that it corresponds to the surface expression of the buried anticline (Fig. 10a) that traps the gas accumulation. Blue line is the topographic profile extracted from the SRTM DEM, whist red line is the smoothed topographic profile.
(2009) shows gently folded layers of Paleozoic rocks (Fig. 10b and c). Moreover, the discovery well 1-RUT-1-AM is located exactly in the center of the Madrub a drainage anomaly (Fig. 11), thus attesting that it corresponds to the surface expression of an underlying anticline (Fig. 10a). The Japiim gas field was discovered in 2001, comprising a 4,5 m thick reservoir at a depth of 1470 m. The production forecast is of 100,000 m3/day (ANP, 2010). In contrast to the Azul~ ao field, Japiim does not spatially coincide with any drainage ~ River in this region is asymmetric anomaly. However, the Uatuma with respect to its floodplain (Figs. 7 and 8), which can be result of rejuvenated obscured or buried structures (Ibanez et al., 2014b). In addition, this field is located in an area with continuous sedimen~ River floodplain), possibly hindering the identifitation (Uatuma cation of subtle topographic expression of geologic structures. Therefore, the overall position of the drainage anomalies in relation to mapped geological structures in the study area corroborates the hypothesis that such features may correspond to the surface expression of buried geological structures. Some of them clearly constitute favorable sites for the search of hydrocarbon traps.
Almeida-Filho, R., Ibanez, D.M., Miranda, F.P., 2010. Interpretaç~ ao morfoestrutural exploraç~ com dados SRTM no auxílio a ao petrolífera: um exemplo na Bacia Sedimentar do Amazonas. Rev. Bras. Geof 28, 89e98. Almeida-Filho, R., Miranda, F.P., 2007. Mega capture of the rio negro and formation ^nia, Brazil: evidences in a SRTM of the Anavilhanas Archipelago, central Amazo digital elevation model. Remote Sens. Environ. 110, 387e392. rio ANP-National Agency of Petroleum, Natural Gas and Biofuels, 2008. Suma ~o accessed 16.09.12. http://maps.bdep. Executivo Externo do Campo de Azula gov.br/website/maps/viewer.htm. rio ANP-National Agency of Petroleum, Natural Gas and Biofuels, 2010. Suma Executivo Externo do Campo de Japiim accessed 29.07.14. http://maps.bdep.gov. br/website/maps/viewer.htm. Araújo, C.C., Yamamoto, J.K., Rostirolla, S.P., Madrucci, V., Tankard, A., 2005. Tar Basin of Brazil: structural and magmatic controls of sandstones in the Parana hydrocarbon charge. Mar. Petrol. Geol. 22, 671e685. Berger, Z., 1994. Satellite Hydrocarbon Exploration: Interpretation and Integration Techniques. Springer-Verlag, Heidelberg, Berlin. Bezdek, J.C., Ehrlich, R., Full, W., 1984. FCM: the fuzzy c-means clustering algorithm. Comput. Geosci. 10, 191e203. Burrato, P., Vannoli, P., Fracassi, U., Basili, R., Valensise, G., 2012. Is blind faulting truly invisible? Tectonic-controlled drainage evolution in the epicentral area of the May 2012, EmiliaeRomagna earthquake sequence (northern Italy). Ann. Geophys. 55, 525e531. Burrough, P.A., van Gaans, P., MacMillan, R., 2000. High resolution landform classification using fuzzy k-means. Fuzzy Set. Syst. 113, 37e52. Burrough, P.A., McDonnell, R.A., 1998. Principles of Geographical Information Systems. Oxford University Press Inc., New York. ~o sobre a Formaç~ ~o e o Alto de Monte Caputo, M.V., 2011. Discussa ao Alter do Cha ~es Alegre. In: Nascimento, R.S.C., Horbe, A.M.C., Almeida, C.M. (Eds.), Contribuiço ^ nia, SBG, Bele m, pp. 7e23. a geologia da Amazo Chauvaud, D., Delfaud, J., 2002. Use of morphostructural analysis to show halokinesis during Mio-Plio-Quartenary in the South-West part of Aquitain Basin. ol. Fr. 173, 317e335. Bull. Soc. Ge ^nica cenozo ica e movimentaça ~o salífera na Bacia do Costa, A.R.A., 2002. Tecto ~es com a geodina ^mica das placas da Ame rica do Sul, Amazonas e suas relaço . Caribe, Cocos e Nazca (Master thesis). Federal University of Para s Cunha, P.R.C., Melo, J.H.G., Silva, O.B., 2007. Bacia do Amazonas. Bol. Geoc. Petrobra 15, 227e251. Deffontaines, B., Chorowicz, J., 1991. Principles of drainage basin analysis from multisource data: application to the structural analysis of the Zaire Basin. Tectonophysics 194, 237e263. cima Rodada de Licitaço ~es e Bacia do Amazonas Dignart, A., Vieira, J.R., 2009. De accessed 21.07.14. http://www.brasil-rounds.gov.br/arquivos/seminarios/STA_
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3_Bacia_do_Amazonas_portugues.pdf. Gonzaga, E.G., Gonçalves, E.T.T., Coutinho, L.E.C., 2000. Petroleum geology of the Amazon Basin, Brazil: modeling of hydrocarbon generation and migration. In: Mello, M.R., Katz, B.J. (Eds.), Petroleum Systems of South America Margins, 73. AAPG Memoir, pp. 159e178. Greenlee, D.D., 1987. Raster and vector processing for scanned linework. Photogramm. Eng. Rem. S. 53, 1383e1387. Hengl, T., 2007. A Practical Guide to Geostatistical Mapping. Office for Official Publications of the European Communities, Luxemberg. Hofton, M., Dubayah, R., Blair, J.B., Rabine, D., 2006. Validation of SRTM elevations over vegetated and non-vegetated terrain using medium footprint lidar. Photogramm. Eng. Remote Sens. 72, 279e285. Holbrook, J., Schumm, S.A., 1999. Geomorphic and sedimentary response of rivers to tectonic deformation: a brief review and critique of a tool for recognizing subtle epeirogenic deformation in modern and ancient settings. Tectonophysics 305, 287e306. Howard, A.D., 1965. Photogeologic interpretation of structure in the Amazon Basin. Geol. Soc. Am. Bull. 76, 395e406. Howard, A.D., 1967. Drainage analysis in geologic interpretation: a summation. Am. Assoc. Pet. Geol. Bull. 84, 2246e2259. Ibanez, D.M., Miranda, F.P., Riccomini, C., 2014a. Geomorphometric pattern recognition of SRTM data applied to the tectonic interpretation of the Amazonian landscape. Photogramm. Eng. Remote Sens. 87, 192e204. Ibanez, D.M., Riccomini, C., Miranda, F.P., 2014b. Geomorphological evidence of recent tilting in the central Amazonia region. Geomorphology 214, 378e387. gico Do IBGE-Brazilian Institute of Geography and Statistics, 2010. Mapa Geomorfolo Estado Do Amazonas accessed 29.07.14. http://geoftp.ibge,gov,br/mapas_ tematicos/geomorfologia/unidades_federacao/am_geomorfologia.pdf. Jenson, S.K., Domingue, J.O., 1988. Extracting topographic structure from digital elevation data for Geographic Information System Analysis. Photogramm. Eng. Remote Sens. 54, 1593e1600. Latrubesse, E., Franzinelli, E., 2002. The Holocene alluvial plain of the middle Amazon river, Brazil. Geomorphology 44, 241e257. Magoon, L.B., Dow, W.G., 1994. The petroleum system. In: Magoon, L.B., Dow, W.G. (Eds.), The Petroleum System - From Source to Trap, 60. AAPG Memoir, pp. 3e24. Mello, M.R., Babinski, N.A., Gonçalves, E.T., Miranda, F.P., 1996. Hydrocarbon prospecting in the Amazon rain forest: application of surface geochemical, microbiological, and remote sensing methods. In: Schumacher, D., Abrams, M.A. (Eds.), Hydrocarbon Migration and its Near-surface Expression, 31. AAPG Memoir, pp. 401e411, 66, Cap. Milani, E.J., Zalan, P.V., 1999. An outline of the geology and petroleum systems of the Paleozoic interior basins of South America. Episodes 22, 199e205. Miranda, F.P., Bentz, C.M., Fonseca, L.E.N., Lima, C.C., Costa, A.R.A., Nunes, K.C., Felgueiras, C.A., Almeida-Filho, R., 1994. Integraç~ ao de dados de sensoriamento ~o do arcabouço estrutural remoto, aeromagnetometria e topografia na definiça
~o do Rio Uatuma ~ (Bacia do Amazonas) (Petrobras Report). da regia Miranda, F.P., Boa Hora, P.P., 1986. Morphostructural analysis as an aid to hydrocarbon exploration in the Amazonas Basin, Brazil. J. Petrol. Geol. 9, 163e178. Mitra, D.S., 2011. Remote sensing and GIS in petroleum exploration. In: Anbazhagan, S., Subramabian, S.K., Yang, X. (Eds.), Geoinformatics in Applied Geomorphology. CRC Press, Florida, pp. 269e290. reas priorit ~o na Neves, C.A.O., 1990. Prospectos potenciais e a arias para exploraça s 4, 95e103. Bacia do Amazonas. Bol. Geoc. Petrobra pez, M., 2006. Morphotectonic criteria for the identiOllarves, R., Audemard, F., Lo fication of active blind thrust faulting in alluvial environments: case studies from Venezuela and Colombia. Z. Geomorphol. 145, 81e103. Pike, R.J., 1995. Geomorphometry - progress, practice and prospect. Z. Geomorphol. 101, 221e238. Pike, R.J., 2000. Geomorphometry - diversity in quantitative surface analysis. Prog. Phys. Geog 24, 1e20. Pike, R.J., Evans, I.S., Hengl, T., 2009. Geomorphometry: a brief guide. In: Hengl, T., Reuter, H.I. (Eds.), Geomorphometry: Concepts, Softwares, Applications. Elsevier, Amsterdam, pp. 3e30. Rabus, B., Eineder, M., Roth, A., Bamler, R., 2003. The Shuttle Radar Topography Mission e a new class of digital elevation models acquired by spaceborne radar. Photogramm. Eng. Remote Sens. 57, 241e262. Rasemann, S., Schmidt, J., Schrott, L., Dikau, R., 2004. Geomorphometry in mountain terrain. In: Bishop, M., Shroder, J.F. (Eds.), GIS in Mountain Geomorphology. Springer, Berlin, pp. 101e146. Raymond, D., Deffontaines, B., Rudant, J.P., Elion, P., Andrieux, J., 1994. Morphostructural analysis, radar and SPOT image interpretation as tool for petroleum zenas area (He rault, South France). exploration: an example from the Gabian-Pe Int. J. Remote Sens. 15, 2469e2479. Reuter, H.I., Hengl, T., Gessler, P., Soille, P., 2009. Preparation of DEMs for geomorphometric analysis. Dev. Soil Sci. 33, 87e120. Rumsey, I.A.P., 1971. Relationship of fractures in unconsolidated superficial deposits to those in the underlain bedrock. Mod. Geol. 3, 25e41. ~o Neto, R., Schobbenhaus, C., Goncalves, J.H., Santos, J.O.S., Abram, M.B., Lea gica Matos, G.M.M., Vidotti, R.M., Ramos, M.A.B., Jesus, J.D.A., 2004. Carta Geolo simo: sistema de informaço ~es geogra ficas d SIG, Brasília. do Brasil ao Milione Seijmonsbergen, A.C., Hengl, T., Anders, N.S., 2011. Semi-automated identification and extraction of geomorphological features using digital elevation data. In: Smith, M.J., Paron, P., Griffiths, J.S. (Eds.), Geomorphological Mapping: Methods and Applications. Elsevier, Amsterdam, pp. 297e335. Teodoro, A.C., Pais-Barbosa, J., Veloso-Gomes, F., Taveira-Pinto, F., 2009. Evaluation of beach hydromorphological behaviour and classification using image classification techniques. J. Coast. Res. 56, 1607e1611. s, J.M., Zech, R., García Morabito, E., 2014. Drainage anomalies Terrizzano, C.M., Corte as indicators of soft-linked deformation zones between neotectonic structural highs in the Precordillera, Central Andes of Argentina. Geomorphology 224, 1e15.
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Marine and Petroleum Geology journal homepage: www.elsevier.com/locate/marpetgeo
Research paper
Analysis of SRTM data as an aid to hydrocarbon exploration in a frontier area of the Amazonas Sedimentary Basin, northern Brazil Delano M. Ibanez a, *, Raimundo Almeida-Filho b, Fernando P. Miranda a a b
cio Macedo, 950, Cidade Universita ria, Ilha do Funda ~o, Rio de Janeiro, Brazil Petrobras Research and Development Center (CENPES), Av. Hora ~o Jos National Institute for Space Research-INPE, C. P. 515, Sa e dos Campos, Brazil
a r t i c l e i n f o
a b s t r a c t
Article history: Received 9 September 2014 Received in revised form 11 December 2015 Accepted 23 March 2016 Available online 28 March 2016
The Shuttle Radar Topography Mission (SRTM) provided an unprecedented source of space-borne topographic information that has shown to be of particular interest for studies in densely vegetated tropical areas, such as Central Amazonia. The digital elevation models produced in that region show subtle details of the terrain that usually appear blurred in conventional remote sensing images. Interpretation of an SRTM-derived drainage network and geomorphometric features revealed several drainage anomalies, which are possibly the surface expression of buried morphostructural features. Integration with geological and geophysical ancillary data strongly suggested that interpreted features constitute potential structural sites for hydrocarbon exploration. However, due to their inferred nature, the structures herein identified are not by themselves a justification for drilling. However, they do provide information for planning seismic surveys, thus reducing costs of the exploration campaigns, as well as minimizing potential environmental impacts of such an enterprise in areas of tropical rain forests. Despite the relatively small size of the study area, it is expected that procedures presented in this paper can be successfully applied throughout the approximately 1,000,000 km2 of sedimentary basins in the Brazilian Amazonian region. © 2016 Elsevier Ltd. All rights reserved.
Keywords: Morphostructural analysis Petroleum exploration SRTM DEM Amazonas basin
1. Introduction Remote sensing technology is nowadays a well-accepted auxiliary tool for hydrocarbon exploration in frontier areas, since it may provide relevant information for planning seismic surveys, thus reducing costs of the exploration campaigns (e.g. Mello et al., 1996; Mitra, 2011), and minimizing potential environmental impacts of such an enterprise. The use of this technology in low-relief sedimentary basins aims at identifying subtle surface expressions of buried structural features that may constitute possible prospecting sites. The term low-relief basin refers here to a sedimentary area, whose stratigraphic and structural features are completely buried by mostly undeformed younger sedimentary units and soils, in addition to the vegetation cover. Under such physiographical conditions, surface expressions of buried structures may be denoted by the local organization of drainage network. The expected arrangement in low relief basins
* Corresponding author. E-mail addresses: [email protected] (D.M. Ibanez), [email protected] (R. Almeida-Filho), [email protected] (F.P. Miranda). http://dx.doi.org/10.1016/j.marpetgeo.2016.03.024 0264-8172/© 2016 Elsevier Ltd. All rights reserved.
filled with a flat-lying sedimentary section is the dendritic pattern, characterized by irregular drainage branching, with tributaries joining main streams at different angles (Howard, 1967). However, as recognized by many authors in diverse climatic and surface conditions (e.g. Howard, 1965; Miranda and Boa Hora, 1986; Deffontaines and Chorowicz, 1991; Berger, 1994; Raymond et al., 1994; Chauvaud and Delfaud, 2002; Araújo et al., 2005; Ollarves et al., 2006; Almeida-Filho et al., 2010; Burrato et al., 2012; Terrizzano et al., 2014), drainage analysis may indicate the presence of buried geological features, which are suggested by specific anomalous patterns relative to the regional network. Therefore, stream alignment, or rectilinear stream segments, may be interpreted as the surface expression of buried faults and fractures. Furthermore, radial and annular drainage patterns, or a combination of them, are of special interest, since they may be associated with subtle surface expressions of buried domal structures that constitute potential hydrocarbon structural traps. The studied area is situated in Central Amazonia, which is unique in terms of general lack of outcrops, extensive rain forest and cloud cover, as well as a generally flat topography. Thus, the application of traditional geomorphological mapping is time
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consuming and costly activity. Moreover, the resolution of available geomorphological mapping (i.e., 1:1,800,000 e IBGE, 2010) does not allow reliable attribution of landforms in a particular hydrographic basin, but at the Amazonas Basin scale only. Therefore, the geomorphological mapping of this region requires semi-automated methods for the identification and classification of terrain features. These landforms can be derived using the SRTM DEM by means of a semi-automated unsupervised method, such as fuzzy k-means clustering approach (e.g. Seijmonsbergen et al., 2011). Thus, in this article, we analyze the drainage network and geomorphometric features extracted from an SRTM digital elevation model, supported by ancillary geological and geophysical information, aiming to identify structures that may constitute potential hydrocarbon prospects in a test-site of the Amazonas Sedimentary Basin, located approximately 100 km east of the city of Manaus (Fig. 1). Such an approach is considered an effective lowcost method for early stages of exploration in the Amazonas Sedimentary Basin, where discoveries have been hindered by a limited availability of seismic data and drilling, as well as by logistical and environmental restrictions imposed by the tropical rain forest.
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Presently there are only two commercial natural gas accumulations in this basin. Nevertheless, the perspectives of new discoveries is good, since the all essential elements of a petroleum system (as defined by Magoon and Dow, 1994) are present in the region (Gonzaga et al., 2000). 2. Geological setting Completely covered by the tropical rain forest of northern Brazil, the Amazonas Sedimentary Basin is about 1300 km long and 350 km wide. The Amazonas River flows approximately along the main central trough of the basin, dividing it into northern and southern flanks. The Amazonas Basin is separated from the Sol~es Basin to the west by the Purus Arch, and from the Marajo imo Arch (Fig. 1a). Igneous and metaBasin to the east by the Gurupa shields morphic Precambrian rocks of the Guiana and Guapore bound the basin to the north and south, respectively (Gonzaga et al., 2000). In the Amazonas Basin, a pile of Paleozoic sediments about 5500 m thick is organized into four sequences, separated by regional unconformities and overlaid by Upper-Cretaceous to
Fig. 1. Location of the study area. (a) Stratigraphic units and tectonic features of northern Brazil (after Schobbenhaus et al., 2004). (b) Detailed view of the study area, showing the main rivers and (A) Azul~ ao and (B) Japiim gas fields, as depicted using the SRTM DEM. Manaus is the capital of the Amazonas State, northern Brazil.
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Fig. 2. Aerial view of the tropical rain forest and of a stream in the Amazonas Basin. The vegetation cover is a hindrance to the application of more classical geomorphological methods.
Quaternary clastic continental deposits (Cunha et al., 2007; Caputo, 2011). Marine shales, sandstones and diamictites of the Trombetas Group constitute the Upper Ordovician-Lower Devonian sequence. In addition, sandstones, siltstones, and shales of the Urupadi and groups represent the Middle Devonian-Lower Carboniferous Curua sequence. The Faro Formation alone is the Middle Carboniferous sequence, which is characterized by fluvial-deltaic sandstones and mudstones with influence and coastal storms. Furthermore, clastic s Group constitute the Middle and chemical rocks of the Tapajo Carboniferous-Permian sequence. The tectonic framework of the Amazonas Basin comprises hinge lines, half-grabens, platforms, and accommodation zones that promote polarity inversion. The Amazonas Basin has a well-developed petroleum system, in which Upper Devonian hydrocarbon source rocks of the Barreirinha Formation up to 150 m thick are widely distributed, with average TOC of 4%, and peak of 10% (Gonzaga et al., 2000). The main reservoir rocks are Carboniferous eolian sandstones of the Monte Alegre Formation and Neocarboniferous sandy basal layers of the
Fig. 3. Conventional SAR image of the study area obtained by the JERS-1 satellite (a), and the corresponding SRTM digital elevation model (b) highlighting details of the drainage network.
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Nova Olinda Formation. Evaporites of the Nova Olinda Formation ~o are the top seals for gas accumulation in sandy layers of the Azula and Japiim fields (Fig. 1b). In addition, carbonates of the Carboniferous Itaituba Formation constitute in the seal for the underlying sandstones of the Monte Alegre Formation (Milani and Zalan, 1999). An Early Jurassic magmatism represented by sills and dikes of basic rocks contributed to the thermal maturity of the source rocks, while tectonic event (Early Jurassic-Early Cretaceous) was the Jurua responsible for the development of compressional structural traps, which are constituted by. asymmetric anticlines in the upthrown blocks of the reverse faults. Traps also occur in asymmetric anticlines on top of upthrown blocks of normal faults developed during the Paleozoic. Stratigraphic traps can also be present where sands pinch out into evaporites. (Neves, 1990; Gonzaga et al., 2000). Seismic data indicate that these structural traps do not deform the deposits of Cretaceous to Quaternary age about 300 m thick (Costa, 2002). The study site is located in the northern flank of the Amazonas Basin, encompassing a surface of approximately 110 km by 70 km that is entirely covered by undisturbed tropical rain forest. The relief consists predominantly of extensive low plateaus differently dissected, but flood plains, fluvial terraces, sandy plains, tabular and hilly surfaces are also observed (Ibanez et al., 2014a). The elevation range is about 150 m between the large floodplains of the Amazonas and Uatum~ a rivers, and the main drainage divides. Geologically, the investigated area is largely occupied by Cenozoic ~o Formation (Fig. 1a), which is made up of rocks of the Alter do Cha quartz arenites coarse to medium grained, locally conglomeratic (Costa, 2002; Caputo, 2011). It is also worth noting that throughout the region's main rivers, there are Quaternary deposits formed by clay and the alluvial plains of sand-rich sediments deposited in the floodplains, levees and abandoned channels (Latrubesse and Franzinelli, 2002). 3. Material and methods 3.1. SRTM data In tropical rain forest regions, radar backscatter at C-band (5.6 cm) results from multiple interactions of the incident wave with components of the vegetation canopy (trunks, branches, twigs, and leaves). Thus, the digital elevation models produced by the SRTM in such areas do not express direct information from the terrain itself, but from the vegetation canopy within the approximately 92 m spatial resolution element of the system (Rabus et al., 2003). Topography is enhanced because the mean height of the tree
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crowns follows the ground surface on a regional scale. Consequently, the resulting digital elevation model reproduces the terrain morphology. In this process, the drainage network is emphasized due to differences in heights between uncovered river surface and the adjacent forest (Fig. 2). The SRTM DEM should nevertheless be used carefully in heavily vegetated areas because there is a positive relationship between elevation error and height of the canopy (Hofton et al., 2006). In this regions, radar waves in the C-band will scatter and deflect upward again, from near the top of the canopy e from 0.5 to 0.75 of the height of the trees (Reuter et al., 2009). Although a DEM derived from topographic maps based on a field survey in heavily vegetated areas that are scarce in the Amazon region will be much more reliable than those derived from radar, an SRTM DEM, on the other hand, always shows much more local detail (such as micro- and meso-relief) (Reuter et al., 2009). Furthermore, SRTM digital elevation models have opened up unprecedented opportunities for studies in densely vegetated tropical areas, because they enhance subtle details of the terrain that are costmarily blurred in conventional remote sensing images (Almeida-Filho and Miranda, 2007). For comparison purposes, Fig. 3 shows the study area through a conventional L-band synthetic aperture radar (SAR) image obtained by the Japanese Earth Resources Satellite-1 (JERS-1), and the corresponding SRTM digital elevation model. Intermediate gray levels in the JERS-1 image represent the intensity of the radar return from the components of the forest canopy (trunks branches, twigs and leaves) with some contribution from the rough ground surface. Light gray levels result from radar double-bounce effect in areas of flooded forests along drainages, and black is associated with free water surfaces that are smooth. In the SRTM digital elevation model, gray levels vary accordingly from darker to lighter shades as the terrain topography increases. Therefore, the value range of the color scale of the SRTM data can be easily adjusted to further emphasize the desired topography features, which is impossible with the radar dataset. The drainage network was automatically extracted from the SRTM digital elevation model using the D8 algorithm presented by Jenson and Domingue (1988) and available in the DWCON tool from PCI software package, version 10.0. Such an approach allows the extraction of a drainage network in raster format. Taking first-order rivers as a reference, the drainage network was geometrically corrected, using a cartographic base provided by the Brazilian Institute of Geography and Statistics (IBGE). In the following step, the drainage network was converted to the vector format using the RTV tool from PCI 10.0 (Greenlee, 1987). This result was then incorporated to a geocoded dataset that included previous geological and
Fig. 4. Surface expression models of drainage arrangements for obscured and buried morphostructural features at initial (a), intermediate (b), and advanced (c) stages of erosion (after Berger, 1994), corresponding, respectively, to the examples identified in the study area: Madruba (d), Aneba (e) and Bacabudo II (f). See Fig. 6b for location.
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~ River region: a) elevation; b) TWI; c) VDepth; d) MRVBF; e) DFM; f) PERC; g) CONI; Fig. 5. A preview of the Land Surface Parameters (LSPs) derived using SRTM DEM for the Uatuma h) OPENNESS. See Fig. 1 for location.
geophysical data available in the study area (faults, drilled wells, and the Bouguer gravity map). 3.2. Drainage anomalies The Paleozoic stratigraphic intervals of exploratory interest in the Amazonas Basin are covered by younger, mostly undeformed Cretaceous to Quaternary sediments. Thus, the analysis of the drainage network aiming at the identification of buried structural features is based on the premise that the present-day landscape may reflect features inherited from the past. Such features would be expressed by subtle arrangements of the drainage network, which would adjust their channel to surface conditions controlled by buried structural features (e.g. Miranda and Boa Hora, 1986). The mechanisms by which subsurface structural features become apparent in recent sediments are not fully understood. It is believed (e.g. Berger, 1994 and references therein) that differences in the type and thickness of sediment in the vicinity of the buried structure can result in differential vertical stresses, which may cause partial reactivation of structures and lead to local increases in topographic relief or increased fracture density at the surface. Lateral variations in the sedimentary column covering buried structures may result in differential compaction and subsidence and thus also lead to local changes in topographic relief or surface fracturing (Rumsey, 1971; Berger, 1994; Holbrook and Schumm, 1999). According to Berger (1994), the geomorphic evolution of a domal feature can be categorized into three erosive stages (Fig. 4): (a) initial, (b) intermediate, and (c) advanced. The initial dissecting of a domal structure is controlled by radial consequent drainages1 that flow to subsequent rivers,2 partially adjusted to the edges of the structure. The intermediate stage of erosion is characterized by the development of a central stream originated from an obsequent drainage3 that evolves through the capture of the consequent radial
1 Consequent is drainage whose course or direction is dependent on or controlled by the general form or slope of the land surface in the dip direction. 2 Subsequent is drainage that has developed its valley adjusted to the regional structure, flowing approximately in the direction of the strike of the underlying strata. 3 Obsequent is drainage that flows in a direction opposite to that of an original consequent drainage, or in a direction opposite to that of the dip of the local strata.
drainages. The advanced stage of erosion results in substantial lowering of the structure, and in the development of a central stream splitting the obscured structural feature, which is now partially suggested by segments of subsequent drainages. Besides illustrating these three models of geomorphic evolution of domal structures, Fig. 4 shows actual examples of correspondent drainage anomalies identified in the study area through the visual analysis of the hydrographic network extracted from SRTM DEM. Taking into account the methodological approach and reasoning discussed above, several drainage anomalies were identified in the study area. The possible geological meaning and potential prospecting significance of these features will be discussed in the sections 4 and 5. 3.3. Semi-automated identification and extraction of geomorphological features Geomorphometry is an interdisciplinary science that combines earth science, mathematics and computation to describe the earth's surface as a numerical representation with quantitative descriptors (Pike, 1995, 2000; Rasemann et al., 2004). The fundamental operation in geomorphometry is the extraction and classification of parameters and objects from digital elevation models (Pike et al., 2009). In this context, geomorphological maps created through photo-interpretation and field observation are gradually being replaced by geomorphological maps that are extracted from DEMs (Seijmonsbergen et al., 2011). In this study, geomorphological classes were optimally extracted using the fuzzy k-means clustering approach as employed by Burrough et al. (2000) and Seijmonsbergen et al. (2011). Firstly, this approach involved the selection of land surface parameters (LSPs) derived from the SRTM DEM in order to explain the distribution of geomorphological classes. The LSPs selected were: elevation, topographic wetness index (TWI), valley depth (VDEPTH), multiresolution valley bottom flatness index (MRVBF), difference from the topographic mean (DFM), residual percentage index of the elevation (PERC), convergence index (CONI) and topographic openness with radii of 250 m (Fig. 5aeh, respectively). These parameters were chosen because they highlight subtle changes in morphology and roughness of regions characterized by low relief (Seijmonsbergen et al., 2011), such as the study area. The LSPs were extracted using the SAGA GIS software (Hengl, 2007).
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The next step was to convert the LSPs into independent components using principal component analysis (PCs). Thus, the 8 original LPSs were converted to 8 PCs in order to reduce potential error introduced through multicollinearity of predictor variables (Hengl, 2007). Therefore, geomorphological classes were extracted of the 8PCs using the fuzzy k-means classification. This unsupervised approach will optimally assign each individual pixel to an abstract class; the class centers were selected in such way that the sum of squares within groups is minimized (Bezdek et al., 1984; Burrough and McDonnell, 1998). After this step, classes editing
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and aggregation were interactively performed to correct possible confusion and misclassification. Finally, in order to improve accuracy and aesthetics, a mode filter 7 7 was applied to the geomorphological classification. The mode filter computes the mode of the gray-level values inside the filter window surrounding each pixel. Mode filtering was utilized for removing small, extraneous islands of data by replacing them with values corresponding to their surroundings, thus eliminating “speckles” (Teodoro et al., 2009).
Fig. 6. Drainage network automatically extracted from the SRTM digital elevation model (a) and identified drainage anomalies (b).
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4. Results 4.1. Drainage anomalies In the Fig. 6a, the study area presents, in general, dendritic to sub-dendritic drainage patterns, with tributaries joining main streams at different angles. However, radial/annular drainage patterns can be identified locally, which may be associated with
buried domal features. In order to avoid any bias, drainage analysis was performed without consulting the geological or geophysical information available in the study area. From this analysis, fourteen drainage anomalies were identified and named after the main stream they are associated with. Stream arrangements that configure these anomalous patterns vary considerably in extension, from about 4 km up to 20 km in diameter (Fig. 6b). Anomalous drainage patterns identified in the study area can be grouped
Fig. 7. Anomalous drainage patterns compared with the results of (a) available geomorphological map of study area (IBGE, 2010) and, (b) the semi-automated unsupervised geomorphological classification, main regional geological features (Neves, 1990), gas fields and wells. Drainage anomalies in the western part correspond mainly to the hilly surface, ~o and (B) Japiim gas fields. whilst the anomalies in the southeastern portion are related to floodplains and mostly sandy plains. Letters indicate the (A) Azula
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Fig. 8. Anomalous drainage patterns compared with the geological map (Schobbenhaus et al., 2004), main regional geological features (Neves, 1990), gas fields and wells. The ~o and (B) Japiim gas fields. drainage anomalies are located on Cenozoic rocks of the Alter do Ch~ao Formation. Letters indicate the (A) Azula
into two main sets. The first one comprises features situated in the western part of the study site, represented by the Tucunarezinho, , Bom Jesus-I, Bom Jesus-II, Bacabudo-I, and Bacabudo-II Aneba drainage anomalies. The other set includes the Maquarazinho, , and Madrub Sanabani-Itabani, Caiaue a drainage anomalies that are located in the southeastern part of the investigated region.
4.2. Geomorphological map The final geomorphological map is shown in Fig. 7. This product is based on the unsupervised classification implemented in the investigated region, which allowed defining 3 kinds of landforms based on 8 LSPs: floodplains, sandy plains and hilly surfaces. Floodplains represent a set of aggradation forms produced by
Fig. 9. Anomalous drainage patterns compared with the Bouguer gravity map and main regional geological features (Neves, 1990). The set of drainage anomalies to west is located along the northern border of a region with low gravity values, which is bounded by a normal fault.
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modern river sedimentation, consisting of seasonally flooded areas that fill the valleys of the main channels. Sandy plains constitute flat surfaces developed above an extremely sandy substrate and are found around valley bottoms and interfluves. Hilly surfaces bring together a set of landforms that are characterized by more intense morphodynamic activity and by a distinctly marked dissection (Ibanez et al., 2014a). These results demonstrate that the Uatum~ a River landscape is more compartmentalized than shown in the available geomorphological map (compare Fig. 7a and b). 5. Discussions Drainage anomalies were compared with ancillary geological and geophysical information with the aim of investigating whether they could be associated with possible buried structural features, or would merely represent surface arrangements without any apparent structural control. They were only observed in Cenozoic ~o Formation (Fig. 8). However, the absence rocks of the Alter do Cha of anomalous features in the north and northeastern portions of the study area may be a consequence of geomorphological dynamics, and not simply an aspect of lithology. These portions mainly correspond to floodplains (Fig. 7). Floodplains are represented by flat surfaces and modern river sedimentation; they thereby can continuously obscure possible traces of domal structures, thus hindering the identification of drainage anomalies associated with these features. Conversely, drainage anomalies in the western and southeastern parts of the investigated site mainly correspond to hilly surface and sandy plains, respectively (Fig. 7). These landforms therefore enhance the surface expression of geological structures. The combination of the Bouguer gravity anomaly map with previously mapped structures and the identified drainage anomalies is shown in Fig. 9. The main feature highlighted in the Bouguer map is a region with low gravity values in the central part of the
studied area, whose northern border is defined by a prominent normal fault mapped by Neves (1990). This NEeSW structural feature that dips southeastward coincides with the boundary of the low-gravity, thus reinforcing the interpretation of a half-graben. The hinge line on the northern flank of the Amazonas Basin dips to the southeast (Gonzaga et al., 2000) and crosses diagonally the southeastern part of the study area, running roughly parallel to the above mentioned normal fault. In this region, seismic data indicated the existence of a set of reverse faults associated with the tectonic event at the top of the Carboniferous seal rocks Jurua (Fig. 10a), which follow the main direction of the hinge line, with upthrown blocks to the southeast (Miranda et al., 1994). Comparison of the two distinct sets of drainage anomalies with the geological information shown in Figs. 7e9 strongly suggests that these features are controlled either by the normal fault defining the northern edge of the gravity low or by the normal fault located along the hinge line. On one hand, the drainage anomalies , Bom Jesus-I, Bom Jesus-II, Bacanamed as Tucunarezinho, Aneba budo-I, and Bacabudo-II constitute a trend of morphostructural features striking NEeSW in the upthrown block of the normal fault. , and On the other hand, Maquarazinho, Sanabani-Itabani, Caiaue drainage anomalies are spatially associated with the Madruba Lucas Borges lineament, with the northern hinge line of the Amazon Basin (Figs. 7e9) and with the reverse faults situated in the southeastern part of the study area (Fig. 10a). With the aim of evaluating the prospective significance of the identified drainage anomalies, we also investigated whether the ~o and Japiim gas fields are located coincidentally with one of Azula ~o gas field, the drainage anomalies (Figs. 7 and 8). The Azula discovered in 1999, comprises a 12 m thick reservoir at a depth of 1650 m. Tests revealed a production potential of 700,000 m3/day, plus a small percentage of condensate (ANP, 2008). Throughout this gas field, a NE-oriented seismic line published by Dignart and Vieira
Fig. 10. a) Drainage anomalies superimposed on the two-way travel time structural map at the top of the Itaituba Formation. Contour interval is 20 ms (modified from Miranda et al., 1994). Drainage anomalies are located along several reverse faults and one anticlinal. b) Selected portion of a NEeSW seismic line (0254-0151 line) that includes well 1-RUT-1AM and illustrates gently folded layers of Paleozoic rocks (modified from Dignart and Vieira, 2009). c) Two-way travel time structural map at the top of the Nova Olinda Formation. Contour interval is 25 ms (modified from Dignart and Vieira, 2009).
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6. Conclusions Analysis of the SRTM-derived drainage network suggested the presence of buried geological structures in a study area of the Amazonas Sedimentary Basin, which encompasses the Uatum~ a River. Combination of a semi-automated unsupervised geomorphological classification of the SRTM data and previous geological information indicates that the identified morphostructural features may constitute hydrocarbon prospective sites. However, because they are defined based solely on geomorphologic inference, the structures herein suggested are not themselves justification for drilling. Conversely, they provide information for planning seismic surveys, thus reducing costs of the exploration campaigns, as well as minimizing the potential environmental impacts of such enterprises in areas of tropical rain forests. The spatial coincidence be drainage anomaly and Azula ~o gas field shows tween the Madruba that procedures discussed in this paper can be successfully applied elsewhere in the Brazilian Amazonia, as well as in other sedimentary basins of the world. Acknowledgments SRTM data were downloaded from the USGS/EROS Data Center (http://eros.usgs.gov/srtm). The JERS-1 SAR image was acquired as part of the Global Rain Forest Mapping Project (GRFM) led by the Earth Observation Research and Application Center (EORC) of the Japan Aerospace Exploration Agency (JAXA). Two anonymous reviewers are appreciated for their helpful comments and suggestions to improve the quality of this paper. References
Fig. 11. a) Ring fence of the Azul~ao gas field (black line) superimposed on the Madruba drainage anomaly (white line - see location in Fig. 6) and well 1-RUT-1-AM. The background corresponds to a shaded relief map derived from the SRTM data. b) Topographic profile along the transect A-B (Fig. 11a). The discovery well 1-RUT-1-AM is located exactly at the center of the morphostrutural feature, attesting that it corresponds to the surface expression of the buried anticline (Fig. 10a) that traps the gas accumulation. Blue line is the topographic profile extracted from the SRTM DEM, whist red line is the smoothed topographic profile.
(2009) shows gently folded layers of Paleozoic rocks (Fig. 10b and c). Moreover, the discovery well 1-RUT-1-AM is located exactly in the center of the Madrub a drainage anomaly (Fig. 11), thus attesting that it corresponds to the surface expression of an underlying anticline (Fig. 10a). The Japiim gas field was discovered in 2001, comprising a 4,5 m thick reservoir at a depth of 1470 m. The production forecast is of 100,000 m3/day (ANP, 2010). In contrast to the Azul~ ao field, Japiim does not spatially coincide with any drainage ~ River in this region is asymmetric anomaly. However, the Uatuma with respect to its floodplain (Figs. 7 and 8), which can be result of rejuvenated obscured or buried structures (Ibanez et al., 2014b). In addition, this field is located in an area with continuous sedimen~ River floodplain), possibly hindering the identifitation (Uatuma cation of subtle topographic expression of geologic structures. Therefore, the overall position of the drainage anomalies in relation to mapped geological structures in the study area corroborates the hypothesis that such features may correspond to the surface expression of buried geological structures. Some of them clearly constitute favorable sites for the search of hydrocarbon traps.
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