Microseepages is one way to identify the existence of oil and gas below the surface of the earth. Identification of microseepages could be done using remote sensing approaches. One of the remote sensing data that can be used is Landsat 8. The purpose of this study is to map the potential of microseepages on the ground surface of Tugu Barat oil and gas field, North West Java Basin, Indonesia. The Landsat 8 data processing were performed including radiometric and geometric corrections, and vegetation indices calculation. The indices calculated in this study are Normalized Differences Vegetation Index (NDVI), Enhanced Normalized Differences Vegetation Index (ENDVI) and Leaf Area Index (LAI). Based on the vegetation indices, we detected that physical condition of vegetation anomaly served as microseepages location. The results showed that microseepages is identified in the south to the east of the oil and gas field presented by vegetation anomaly. Field survey confirmed the possibility of microseepages is located at yellowish leaf vegetation, high spectral of the leaf at the visible wavelength and low magnetic susceptibility.

This study tried to monitor sugar cane condition surrounding of oil and gas field area. The spectral approaches were conducted for mapping sugar cane stress. As an initial stage Landsat-8 was corrected radiometrically and geometrically. Radiometric correction is an important stages for spectral approaching. Then all pixel values were transformed to the surface reflectance. Several vegetation indices were calculated to monitor vegetation stress surrounding of oil and gas field. NDVI, EVI, DVI, GVI, GRVI, GDVI and GNDVI were applied for generating tentative sugar cane stress images. The results indicated that sugar cane surrounding of oil and gas field has been influenced by oil and gas field.

Heavy Metal Contamination in the Coastal Area of Tanjung Selor North Kalimantan. The establishment of the North Kalimantan Province transformed the Tanjung Selor region and its surroundings into the provincial capital so that it will grow rapidly, both in terms of development and other activities. Monitoring environmental conditions, one of which is heavy metals in the waters need to be carried out as a starting environment before the area develops. This is important given the nature of heavy metals that change toxic at concentrations that exceed the threshold. The purpose of this study is to identify the potential for heavy metal contamination in the coastal area of Tanjung Selor, Bulungan Regency, North Kalimantan Province. Heavy metals studied is limiting to mercury (Hg), Chromium (Cr), Arsenic (As), Cadmium (Cd), Copper (Cu), Lead (Pb) and Zinc (Zn). The location of the sampling was carried out using Landsat 8 imagery designed to represent the condition of the coastal area. Samples come from well water, river water, seawater, and marine sediments at 4, 9 and 5 observation stations respectively. Samples were taken on August 2014 using the grab sample method and analyzed for heavy metal content using the standard American Public Health Association (APHA) method with the Atomic Absorption Spectroscopy (AAS) instrument. Of the 23 samples produced, only 3 observation stations were not contaminated with heavy metals. While in the other 20 samples one of three types of heavy metals were found that exceeded the threshold. In general, Cu is the most detected metal exceeding the threshold in the study area found in samples of river water, sea water and sediment. Zn is found to exceed the threshold in well water. Pb is found to exceed the threshold in sample 5 of river water. Cd is found to exceed the threshold in samples of river water, sea water and sediment. The source of pollution is thought to originate from coal mining activities, oil palm plantations, and household waste. The overall results of this study show that river estuaries tend to accumulate heavy metals.

Microseepages is one way to identify the existence of oil and gas below the surface of the earth. Identification of microseepages could be done using remote sensing approaches. One of the remote sensing data that can be used is Landsat 8. The purpose of this study is to map the potential of microseepages on the ground surface of West Tugu oil and gas field, North West Java Basin, Indonesia. The Landsat 8 data processing were performed including radiometric and geometric corrections, and vegetation indices calculation. The vegetation indices calculated in this study are Normalized Differences Vegetation Index (NDVI), Enhanced Normalized Differences Vegetation Index (ENDVI) and Leaf Area Index (LAI). Based on the vegetation indices, we detected that physical condition of vegetation anomaly served as microseepages location. The results showed that microseepages is identified in the south to the east of the oil and gas field presented by vegetation anomaly. Field survey confirmed the possibility of microseepages is located at yellowish leaf vegetation, high spectral of the leaf at the visible wavelength and low magnetic susceptibility.

Clay minerals in the oil and gas field have changed with an increase of the quantities in the middle of the oil and gas field and reduction in the edges. This reduction is the effect of micro seepage from oil and gas from the subsurface. The aims of the research is to identify the potential oil and gas seepage through clay mineral mapping. The data used where Landsat 8 OLI/TIRS with recording dated September 25, 2015. The method used in the mapping of clay minerals using the ratio of 1.55-1.75 µm (Short Wave Infrared 1) and 2.08-2.35 µm (Short Wave Infrared 2). The result of Landsat 8 OLI/TIRS data processing shows the potential of anomalies in edges of the oil and gas field. The anomaly is a change in the index value of clay minerals that tend to be lower with values 1.0 to 1.5 than the middle of oil and gas field with values 1.5 to 2.0. The potential pattern of the anomaly follows the border of the oil and gas field. Field surveys show that oil and gas field based on grain size analysis is dominated by clay-sized soil. The dominant clay minerals from X-Ray Diffraction analysis are smectite (56%) and kaolinite (6%).