Detection of Hydrocarbon Microseepage in a Rain Forest Environment (Jurua Gas Field, Nonhero Brazil) Using Landsat MSS Data: ABSTRACT

The fundamental assumption of many successful geochemical and geomicrobial technologies developed in the last 80 years is that hydrocarbons leak from subsurface accumulations vertically to the surface. Driven by buoyancy, the process involves sufficiently large volumes directly measurable or indirectly inferable from their surface expressions. Even when the additional hydrocarbons are not measurable, their presence slightly changes the environment, where complex microbial communities live, and acts as an evolutionary constraint on their development. Since the ecology of this ecosystem is very complicated, we propose to use the full-microbiome analysis of the shallow sediments samples instead of targeting a selected number of known species, and the use of machine learning for uncovering the meaningful correlations in these data. We achieve this by sequencing the microbial biomass and generating its DNA fingerprint, and by analyzing the abundance and distribution of the microbes over the dataset. The proposed technology uses machine learning as an accurate tool for determining the detailed interactions among the various microorganisms and their environment in the presence or absence of hydrocarbons, thus overcoming data complexity. In a proof-of-technology study, we have taken more than 1000 samples in the Neuqu謠Basin in Argentina over three distinct areas, namely, an oil field, a gas field, and a dry location outside the basin, and created several successful predictive models. A subset of randomly selected samples was kept outside of the training set and blinded by the client operator, providing the means for objectively validating the prediction performance of this methodology. Uncovering the blinded dataset after estimating the prospectivity revealed that most of these samples were correctly predicted. This very encouraging result shows that analyzing the microbial ecosystem in the shallow sediment can be an additional de-risking method for assessing hydrocarbon prospects and improving the Probability Of Success(POS) of a drilling campaign.

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ARKEOFAUNA KAWASAN KARST BONTOCANI KABUPATEN BONE SULAWESI SELATAN

JURNAL WALENNAE ◽

10.24832/wln.v16i1.314 ◽

2018 ◽

Vol 16 (1) ◽

pp. 21

Author(s):

Nfn Fakhri

Keyword(s):

Data Collection ◽

Environmental Change ◽

Comparative Studies ◽

Rain Forest ◽

Data Availability ◽

Karst Area ◽

Forest Environment ◽

Faunal Composition ◽

Wide Range ◽

Bone Fragments

This study aims to provide a description of the fauna that once interacted with a human in the Bontocani karst Area in Bone District. Of the few excavated sites providing data availability of bone fragments that can be analyzed by conducting comparative studies with existing faunal composition of the fauna. The method of data collection is by excavation at some sites in this Karst Area. The results of this study document a wide range of vertebrates in the Balang Metti fauna including fish, frogs/toads, lizards, snakes, birds, Strigocuscus, Ailurops ursinus, insectivorous bats, Sulawesi monkeys, rats, Sulawesi pigs, babirusa and Anoa. In some layers of culture, the absence of anoa, indicates the environmental change from the environment of the fields and the weeds to the wet rain forest environment around the site, along with the extinction of this fauna. Based on the identified fauna bone analysis, it is illustrated that past habitats and environments in Bontocani Karst area have not changed much. Penelitian ini bertujuan memberikan gambaran secara lebih jelas tentang fauna-fauna yang pernah berinteraksi dengan manusia pendukung kebudayaan yang ada di Kawasan Karst Bontocani di Kabupaten Bone. Beberapa situs yang telah diekskavasi memberikan ketersediaan data berupa fragmen tulang yang dapat dianalisis dengan melakukan studi komparasi dengan komposisi tulang fauna yang ada saat ini. Metode pengumpulan data yang dilakukan adalah dengan ekskavasi di beberapa situs yang ada di Kawasan Karst ini. Hasil penelitian menunjukkan bahwa sebagian besar jenis fauna yang ditemukan di situs ini adalah fauna bertulang belakang antara lain: ikan, kodok/katak, kadal, ular, burung, strigocuscus, Ailurops ursinus, kelelawar pemakan serangga, monyet sulawesi, tikus, babi sulawesi, babi russa dan anoa. Pada beberapa lapisan budaya, tidak adanya temuan fauna anoa, menunjukkan perubahan lingkungan dari lingkungan padang dan ilalang menjadi lingkungan hutan hujan basah di sekitar situs, seiring dengan punahnya fauna ini. Berdasarkan analisis tulang fauna yang berhasil diidentifikasi digambarkan bahwa habitat dan lingkungan masa lampau di Kawasan Karst Bontocani tidak banyak mengalami perubahan.

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Ozone measurements in the troposphere of an Amazonian rain forest environment

Journal of Geophysical Research Atmospheres ◽

10.1029/jd093id12p15850 ◽

1988 ◽

Vol 93 (D12) ◽

pp. 15850 ◽

Cited By ~ 32

Author(s):

V. W. J. H. Kirchhoff ◽

E. V. Browell ◽

G. L. Gregory

Keyword(s):

Rain Forest ◽

Forest Environment ◽

Amazonian Rain Forest

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Introduction of the rain-forest speciesAraucaria cunninghamii ait. To a dry sclerophyll forest environment

Plant and Soil ◽

10.1007/bf01373390 ◽

1967 ◽

Vol 27 (2) ◽

pp. 201-216 ◽

Cited By ~ 7

Author(s):

B. N. Richards

Keyword(s):

Rain Forest ◽

Forest Environment ◽

Sclerophyll Forest

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Aggregation and synecology of arboreal arthropods associated with an overstorey rain forest tree in Australia

Journal of Tropical Ecology ◽

10.1017/s026646740000660x ◽

1992 ◽

Vol 8 (3) ◽

pp. 317-327 ◽

Cited By ~ 5

Author(s):

Yves Basset

Keyword(s):

Rain Forest ◽

Forest Tree ◽

High Variability ◽

Arthropod Community ◽

Forest Environment ◽

Predator Prey ◽

Tree Phenology ◽

Single Well ◽

Arthropod Predator ◽

Arboreal Arthropods

ABSTRACTThe cohesion of the arthropod community associated with the rain forest tree Argyrodendron actinophyllum was studied in a warm subtropical rain forest in Australia. The distribution of most arthropods was contagious on the foliage of A. actinophyllum. Chewers and phloem-feeders were more clumped than epiphyte grazers and parasitoids. Arthropod predator-prey ratios were high and relatively constant over time, as revealed by measures of their activity. However, similar ratios in abundance and species-richness of arthropods foraging on foliage showed high variability in space and no consistent trends. Species associations on the foliage were difficult to predict and did not constitute either a single, well-united community or well-delimited subcommunitics. Most of the data suggest that on the foliage of A. actinophyllum, the cohesion of the arthropod community is not extremely strong. Apart from methodological constraints, possible reasons for this include the influence of host-tree phenology, and the high arthropod-diversity of the rain forest environment.

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Site occupancy and density of sympatric Gaboon viper (Bitis gabonica) and nose-horned viper (Bitis nasicornis)

Journal of Tropical Ecology ◽

10.1017/s0266467406003397 ◽

2006 ◽

Vol 22 (5) ◽

pp. 555-564 ◽

Cited By ~ 29

Author(s):

Luca Luiselli

Keyword(s):

Logistic Regression ◽

Regression Model ◽

Rain Forest ◽

Logistic Regression Model ◽

Distance Sampling ◽

Site Occupancy ◽

Information Criterion ◽

Habitat Types ◽

Forest Environment ◽

Swamp Forest

The presence and density of two sympatric, large-sized vipers (the Gaboon viper, Bitis gabonica and the nose-horned viper, Bitis nasicornis) were studied along several transects, during both dry and wet seasons, and at different times of day, in southern Nigeria (West Africa). Three habitat types were found along the various transects (mature rain forest (MF), secondary rain forest (SF), swamp forest (SW)). The detection probabilities for these vipers were modelled with a set of competing models, and the various models were ordered by Akaike Information Criterion procedures. Two classes of models were used: the single-season model, and the multi-species model. The best models (single-season model) suggested that: for the Gaboon viper, habitat types SF and SW were particularly important in detecting this species, especially during the rainy season at 08h00–16h00. For nose-horned vipers, the best models had SW and MF as site-covariates. Application of the multi-species model revealed that there were different detection functions if both species are present at a site, with a ‘negative’ interaction of occupancy between the species. Females and males were similarly detectable in a logistic regression model, but feeding status and pregnancy slightly increased detection probability in a logistic regression model. Viper density was modelled by a DISTANCE sampling procedure. The density of one species tended to be inversely correlated to the density of the other, suggesting that (1) the rain-forest environment does not support abundant populations of both vipers when sympatric, and (2) the two Bitis species subtly partition the habitat resources.

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