Evaluating the Implications of Lineaments on Petroleum Fields: South Sumatra, Indonesia

Declining oil prices has led to a reduction of petroleum exploration as oil production as no longer a lucrative area of investment as in the previous years. Current exploration activities are supported by field work which are intensive considering the resources required. There is need to develop low cost methods to delineate areas of potential hydrocarbon resources. This research uses Land Satellite (Landsat) 8 Operational Land Imager (OLI) for alteration extraction, Shutter Radar Topography Mission (SRTM) for lineament extraction, Geological maps to develop a low cost method of petroleum exploration. The results indicate high OH bearing alterations on the Gumai and Kasai formation, a seal rock. Extensional tectonics is responsible for the migration of petroleum from the subsurface. It is suggested that future exploration be concentrated on the Gumai and Kasai formation based on evidence of micro seepage.

Automatic Lineaments Extraction using the Line Algorithm in the Denguélé District (North West of Ivory Coast)

The aim of this work was to apply the LINE Algorithm (Segment Extraction Algorithm) on Landsat 8 images for automatic lineament extraction in the Denguélé district. The Landsat 8 images had previously been subjected to the technique of Principal Component Analysis (PCA). After that, we implemented the LINE algorithm. Indeed, the LINE algorithm uses the following six (6) parameters : RADI (Radius of the filter) for improving the quality of the input image, GTHR (Threshold of the contour gradient), LTHR (Threshold of the contour length), FTHR (Threshold of mounting error), ATHR (Angular difference threshold between two contours ) and DTHR (Distance chaining threshold to link two contours ) for lineament discrimination. Analysis of the principal components PCA 1, PCA2 and PCA3 of bands 1, 2, 3, 4, 5 and 7 of the Landsat 8 images shows that they contain respectively 79.57; 15.88 and 2.15%, this represents overall 97.6% of all channels. 3468 lineaments were extracted. The minimum and maximum lengths of the lineaments extracted are respectively 4201.08 m and 16167.59 m and their cumulative length is 18 919 517.9 m. The lineaments average lengths are 5.55 km; 5.75 km; 5.6 km and 5.40 km respectively for NE-SW, NS, E-W and NW-SE directions. The analysis of the directions of the lineaments using a rose diagram with 10 ° of frequency, shows that the dominant directions are NE-SW (31.83% of the total lineaments), EW (28.71% of the total lineaments) and NS (27.91% of the total lineaments).

Lithological, structural and hydrothermal alteration mapping utilizing remote sensing datasets: a case study around Um Salim area, Egypt

Remote sensing datasets have introduced remarkable advancements in mapping rock units, structural elements, and hydrothermal alteration zones. This study applied Landsat Operational Land Imager (OLI) multispectral dataset in discriminating the intricate basement of Um Salim area, Central Eastern Desert (CED), Egypt. Moreover, a panchromatic 15m pixel size band is implemented to extract the study area’s linear structural features. Several image processing methods including False Color Combination (FCC), Band Ratio (BR), Optimum Index Factor (OIF), and Density slicing were utilized in lithological and alteration mapping. The widely used, LINE module of the PCI Geomatica is applied for lineament extraction. Results reasonably discriminate the complicated rock units using selected composites depending on OIF results. A photo-geological map is constructed and shows greater coincidence with recently published maps. Lineaments map and its density revealed the preponderance of NE-SW and WNW-ESE structural trends. The spatial relationship between the resultant hydrothermally-altered zones and the detected structural features strongly recommends further detailed examination for ore deposits within the study area besides manifesting the efficiency of the utilized data and methods.

Lineament Extraction using Gravity Data in the Citarum Watershed

Lineament is one of the most important features showing subsurface elements or structural weakness such as faults. This study aims to identify subsurface lineament patterns using automatic lineament in Citarum watershed with gravity data. Satellite gravity data were used to generate a sub-surface lineament. Satellite gravity data corrected using Bouguer and terrain correction to obtain a complete Bouguer anomaly value. Butterworth filters were used to separate regional and residual anomaly from the complete Bouguer anomaly value. Residual anomaly gravity data used to analyze sub-surface lineament. Lineament generated using Line module in PCI Geomatica to obtain sub-surface lineament from gravity residual value. The orientations of lineaments and fault lines were created by using rose diagrams. The main trends observed in the lineament map could be recognized in these diagrams, showing a strongly major trend in NW-SE, and the subdominant directions were in N-S. Area with a high density of lineament located at the Southern part of the study area. High-density lineament might be correlated with fractured volcanic rock upstream of the Citarum watershed, meanwhile, low-density lineament is associated with low-density sediment. The high-density fracture might be associated with intensive tectonics and volcanism.

Lithological mapping and automatic lineament extraction using Aster and Gdem data in the Imini-Ounilla-Asfalou district, South High Atlas of Marrakech, Morocco

Lithological and lineament mapping using remote sensing is a fundamental step in various geological studies, as it forms the basis for the interpretation and validation of the results obtained. There were two objectives for this study, applied in the Imini-Ounilla-Asfalou district, South High Atlas of Marrakech region: first, lithological mapping by satellite image processing techniques such as ASTER L1B (hight spectral and spatial resolution), namely Principal Component Analysis (PCA), Minimum Noise Fraction (MNF), as well as the application of three types of supervised classification, namely Spectral Angle Mapper (SAM), Maximum Likelihood (ML) and Minimum Distance (MD), on the visible/near-infrared (VNIR) and short-wave infrared (SWIR) spectral bands of our ASTER image; second, an analysis of the distribution of lineaments by automatic extraction using a Global Digital Elevation Model (GDEM) and the PC1 image derived from the PCA transformation applied to the satellite image. The best results are highlighted by the delineation of new facies in relation to the existing map; after confirmation in the field, all of these facies, which include Eocene, Triassic and Jurassic formations, are represented on the new map. The results of lineaments showed that each of them systematically shows a similarity in terms of concentration and orientation, with four preferential oriented systems: NE-SW, E-W, NNE-SSW and NW-SE. The lineaments mainly follow those of the major fault zones, with high concentrations in the northeast and southwest parts of the study area.