scholarly journals Median Polish Kriging and Sequential Gaussian Simulation for the Spatial Analysis of Source Rock Data

2021 ◽  
Vol 9 (7) ◽  
pp. 717
Author(s):  
Emmanouil A. Varouchakis
Keyword(s):  
Spatial Distribution ◽  
Organic Carbon ◽  
Total Organic Carbon ◽  
Source Rock ◽  
Sequential Gaussian Simulation ◽  
Kriging Method ◽  
Geostatistical Model ◽  
Median Polish ◽  
Weight Concentration ◽  
Gaussian Simulation

In this technical note, a geostatistical model was applied to explore the spatial distribution of source rock data in terms of total organic carbon weight concentration. The median polish kriging method was used to approximate the “row and column effect” in the generated array data, in order for the ordinary kriging methodology to be applied by means of the residuals. Moreover, the sequential Gaussian simulation was employed to quantify the uncertainty of the estimates. The modified Box–Cox technique was applied to normalize the residuals and a cross-validation analysis was performed to evaluate the efficiency of the method. A map of the spatial distribution of total organic carbon weight concentration was constructed along with the 5% and 95% confidence intervals. This work encourages the use of the median polish kriging method for similar applications.

scholarly journals The Lithofacies of Pandua Formation Shale in the Andowia Area, North Konawe, Southeast Sulawesi and Its potential as Petroleum source rock

2021 ◽  
Vol 325 ◽  
pp. 08013
Author(s):  
Mawar Towan Lestari Ramli ◽  
Hendra Amijaya ◽  
Akmaluddin
Keyword(s):  
Organic Carbon ◽  
Total Organic Carbon ◽  
Source Rock ◽  
Depositional Environment ◽  
Petrographic Analysis ◽  
Hydrocarbon Accumulation ◽  
High Concentration ◽  
Area North ◽  
Excellent Source ◽  
Petroleum Source Rock

Research on the Late Miocene of Pandua Formation shale in Andowia area, Southeast Sulawesi is fundamental because it is considered to have the potential as a source rock in Manui Basin. This study aimed to determine the lithofacies and its potential as petroleum source rock using megascopic, petrographic, and total organic carbon analyses in Pandua Formation shale. Based on the megascopic and petrographic analysis of outcrops, the shale can be subdivided into 11 lithofacies consists of clayey shale, massive claystone, clastic detritus-rich claystone, massive mudstone, mica-rich mudstone, iron oxide-rich mudstone, low-angle laminated mudstone, massive siltstone, carbon-rich massive siltstone, laminated siltstone, and carbon-rich laminated siltstone. The results of the analysis of 19 samples of shale showed that the total organic carbon (TOC) content was classified as poor to excellent (<0.5%- >4%). The lithofacies with a high concentration of TOC are carbon-rich massive siltstone and carbon-rich laminated siltstone. Both lithofacies were categorized as potentially excellent source rock which the TOC value content is 5.78% and 5.74%.The result implies the better understanding of the depositional environment and hydrocarbon accumulation potential of the Manui basin for future exploration.

scholarly journals Total Organic Carbon (TOC) Value Prediction in Source Rock Potential at North East Java Basin, Indonesia

2021 ◽  
Vol 6 (3) ◽  
pp. 147-151
Author(s):  
Paulus Leonardo Manurung ◽  
Rahmat Catur Wibowo ◽  
Ordas Dewanto
Keyword(s):  
Organic Carbon ◽  
Total Organic Carbon ◽  
Source Rock ◽  
Vitrinite Reflectance ◽  
Excellent Quality ◽  
North East ◽  
The North ◽  
Sonic Log ◽  
Maturity Variable ◽  
Resistivity Log

This research aims to determine the potential of the source rock in the Kujung and Cepu Formations in the North East Java Basin, using Total Organic Carbon (TOC). TOC is calculated using the Passey method. The Passey method is used by overlaying the sonic log and the resistivity log and determining the baseline to get the separation of Δlog resistivity, which is then used to predict the TOC log by including the LOM (Level of Organic Maturity) variable obtained from the data of vitrinite reflectance. After the TOC log value is obtained, a correlation is made with the TOC core value. The prediction result of TOC log in a PM-1 well is 2.16%, which means it has excellent quality. The prediction of TOC log in a PM-2 well is worth 2.68%, which means it has excellent quality. The correlation value between the TOC log and the TOC core of the PM-1 well is 0.67, which means the correlation is strong. In PM-2 well, the correlation between the TOC log and TOC core is 0.92, which means that the correlation is robust.

Lithofacies-dependent rock physics templates of an unconventional shale reservoir on the North Slope, Alaska

2020 ◽  
pp. 1-49
Author(s):  
Minh Tran ◽  
Tapan Mukerji ◽  
Allegra Hosford Scheirer
Keyword(s):  
Organic Carbon ◽  
Total Organic Carbon ◽  
Source Rock ◽  
Velocity Ratio ◽  
Rock Physics ◽  
Hydrogen Index ◽  
Source Rocks ◽  
Rock Properties ◽  
North Slope ◽  
Petrophysical Properties

Over the past 20 years, oil and gas companies have turned their attention to producing petroleum directly from organic-rich shale. Successful exploration, appraisal, and production strategies for source rocks critically depend on reliable identification of their organic components (kerogen, in particular) and generation potential. There is mounting demand to evaluate organic richness in terms of quantity (i.e. total organic carbon) and quality (i.e. hydrogen index) from seismic data, which is usually the only source of information in the early development period of emerging shale plays. We delineated major seismic lithofacies on the Alaska North Slope using elastic, seismic, and petrophysical properties. We performed a well-established quantitative seismic interpretation workflow to integrate geochemical data in the lithofacies definition. Rock physics templates of seismic parameters, Acoustic Impedance, (AI), versus P-wave to S-wave velocity ratio, (VP/VS), are constructed for each lithofacies to assess variations in pore fluid and lithology. We proposed correlations between source rock properties (hydrogen index, total organic carbon) and petrophysical properties (bulk density, porosity, sonic velocity ratio) of the major lithofacies. These correlations, together with facies-specific rock physics templates, can be utilized to predict organic richness and source rock properties away from drilled wells. The models are validated by training data from 2 regional wells to observe their applicability on the Alaska North Slope.

scholarly journals Modelling of maturation, expulsion and accumulation of bacterial methane within Ravneš Member (Pliocene age), Croatia onshore

2016 ◽  
Vol 8 (1) ◽  
Author(s):  
Marko Cvetković
Keyword(s):  
Source Rock ◽  
Sequential Gaussian Simulation ◽  
Shallow Gas ◽  
Early Pliocene ◽  
Reservoir Rocks ◽  
Gas Accumulation ◽  
Large Source ◽  
Hydrocarbon Component ◽  
Potential Source ◽  
Gaussian Simulation

AbstractBacterial methane is a dominant hydrocarbon component in the Northern Croatia’s Adriatic offshore proven hydrocarbon reservoirs. As onshore reserves are declining the potential of shallow gas accumulation, analogue to the Adriatic ones, are being tested. A part of the Lonja Formation (Pliocene Pleistocene and Holocene), the Ravneš Member (Early Pliocene age) is analysed for its maturation and expulsion regarding bacterial methane as potential source and reservoir rocks, especially as it is thermally immature. Two approaches were used for the initial lithology modelling processes - the convergent interpolation and sequential Gaussian simulation. Possibility for trapping and forming of accumulations was also modelled. Results show that selected member has a large source rock potential for bacterial methane with a total volume of 411.53 × 10

Uncertainty assessment of soil organic carbon content spatial distribution using geostatistical stochastic simulation

Soil Research ◽  
2010 ◽  
Vol 48 (1) ◽  
pp. 27 ◽  
Author(s):  
Masoomeh Delbari ◽  
Willibald Loiskandl ◽  
Peyman Afrasiab
Keyword(s):  
Spatial Distribution ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Stochastic Simulation ◽  
Uncertainty Assessment ◽  
Sequential Gaussian Simulation ◽  
Organic Carbon Content ◽  
Spatial Continuity ◽  
Standard Deviations ◽  
Simulation Algorithms

Soil organic carbon (SOC) affects many processes in soil. The main objective of this study was the prediction and uncertainty assessment of the spatial patterns of SOC through stochastic simulation using 2 simulation algorithms, sequential Gaussian simulation (sGs) and sequential indicator simulation (sis). The dataset consisted of 158 point measurements of surface SOC taken from an 18-ha field in Lower Austria. Conditional stochastic simulation algorithms were used to generate 100 maps of equiprobable spatial distribution for SOC. In general the simulated maps represented spatial distribution of SOC more realistically than the kriged map, i.e. overcoming the smoothing effect of kriging. Unlike sGs, sis was able to preserve the connectivity of extreme values in generated maps. The SOC simulated maps generated through sGs reproduced the sample statistics well. The reproduction of class-specific patterns of spatial continuity of SOC for the simulated model produced through sis was also reasonably good. The results highlight that when the class-specific patterns of spatial continuity of the attribute must be preserved, sis is preferred to sGs. For local uncertainty, standard deviations obtained using kriging varied much less across the study area than those obtained using simulations. This shows that the conditional standard deviations achieved through simulations depend on data values in addition to data configuration for greater reliability in reporting the estimation precision. Further, according to accuracy plots and goodness statistic, G, sis performs the modelling uncertainty better than sGs. The simulated models can provide useful information in risk assessment of SOC management in Lower Austria.

scholarly journals Soil organic carbon prediction with terrain derivatives using geostatistics and Sequential Gaussian simulation

2021 ◽  
Author(s):  
Kingsley John ◽  
Isong Abraham Isong ◽  
Ndiye Michael Kebonye ◽  
Prince Chapman Agyeman ◽  
Ayito Esther Okon ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Sequential Gaussian Simulation ◽  
Gaussian Simulation

scholarly journals Spatiotemporal changes in cropland soil organic carbon in a rapidly urbanizing area of southeastern China during 1980-2015

2021 ◽  
Author(s):  
Enze Xie ◽  
Xiu Zhang ◽  
Fangyi Lu ◽  
Yuxuan Peng ◽  
Yongcun Zhao
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Agricultural Development ◽  
Urban Expansion ◽  
Management Strategies ◽  
Crop Productivity ◽  
Sequential Gaussian Simulation ◽  
Soil C ◽  
Spatiotemporal Changes ◽  
Gaussian Simulation

Understanding the spatiotemporal changes in soil organic carbon (SOC) and their driving factors is an important prerequisite for decision-making in maintaining sustainable agricultural development and addressing climate change. A total of 1219 cropland topsoil SOC data (0-20 cm) collected from southern Jiangsu Province of China in 1980, 2000, and 2015, and geostatistical sequential Gaussian simulation were used to identify the changes in the spatiotemporal patterns of SOC during the period of 1980-2015. Results showed that the changes in SOC within the different time periods were significantly different, with a net increment of 3.65 g kg-1 during the period of 1980-2000 and a net decrement of 2.32 g kg-1 during the period of 2000-2015. Significant SOC accumulation occurred throughout the study area during 1980-2000, while SOC decline became predominant in the southeast during 2000-2015. Overall, the SOC contents for 60% of the study area increased significantly over the entire 35-year period. The SOC increase during the first two decades (1980-2000) was largely attributed to the increasing soil C input that resulted from the enhanced crop productivity by chemical fertilizers, while the stagnant soil carbon inputs associated with the rapid urban expansion were the primary reason for constraining cropland SOC accumulation in the subsequent 15 years (2000-2015). These findings highlight the importance of balancing agricultural development and urbanization processes to maintain SOC levels, and may also provide some guidance for planning cropland soil C management strategies in many areas that are undergoing similar urbanization processes.

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