Inference of Q-Values below 1 Hz from Borehole and Surface Data in the Osaka Basin by Three-Component Waveform Fitting

2007 ◽  
Vol 97 (4) ◽  
pp. 1267-1278 ◽  
Author(s):  
K. Yamada ◽  
M. Horike
Keyword(s):  
Surface Data ◽  
Osaka Basin ◽  
Q Values ◽  
Waveform Fitting

The Grobogan Mud Volcano Complex: An Identification to Reveal the Opportunity of Hydrocarbon Exploration

2020 ◽  
Author(s):  
C. Jatu
Keyword(s):  
Water Analysis ◽  
Middle Eocene ◽  
Research Result ◽  
Hydrocarbon Exploration ◽  
System Model ◽  
Mud Volcano ◽  
Hydrocarbon Potential ◽  
Mud Volcanoes ◽  
Central Java ◽  
Surface Data

Mud volcanoes in Grobogan are referred as the Grobogan Mud Volcanoes Complex in Central Java where there is evidence of oil seepages. This comprehensive research is to determine the characteristics and hydrocarbon potential of the mud volcanoes in the Central Java region as a new opportunity for hydrocarbon exploration. The Grobogan Mud Volcano Complex consists of eight mud volcanoes that have its characteristics based on the study used the geological surface data and seismic literature as supporting data on eight mud volcanoes. The determination of geological surface characteristics is based on geomorphological analysis, laboratory analysis such as petrography, natural gas geochemistry, water analysis, mud geochemical analysis and biostratigraphy. Surface data and subsurface data are correlated, interpreted, and validated to make mud volcano system model. The purpose of making the mud volcanoes system model is to identify the hydrocarbon potential in Grobogan. This research proved that each of the Grobogan Mud Volcanoes has different morphological forms. Grobogan Mud Volcanoes materials are including muds, rock fragments, gas, and water content with different elemental values. Based on this research result, there are four mud volcano systems models in Central Java, they are Bledug Kuwu, Maesan, Cungkrik, and Crewek type. The source of the mud is from Ngimbang and Tawun Formation (Middle Eocene to Early Miocene) from biostratigraphy data and it been correlated with seismic data. Grobogan Mud Volcanoes have potential hydrocarbons with type III kerogen of organic matter (gas) and immature to early mature level based on TOC vs HI cross plot. The main product are thermogenic gas and some oil in relatively small quantities. Water analysis shows that it has mature sodium chloride water. This analysis also shows the location was formed within formations that are deposited in a marine environment with high salinity. Research of mud volcanos is rarely done in general. However, this comprehensive research shows the mud volcano has promising hydrocarbon potential and is a new perspective on hydrocarbon exploration.

Smoothing Surface Data by Spline Functions.

1985 ◽  
Author(s):  
P. C. Stein ◽  
W. L. White
Keyword(s):  
Spline Functions ◽  
Surface Data

Prediction based on response surface data obtained with random blocking

Test ◽  
1994 ◽  
Vol 3 (2) ◽  
pp. 87-99
Author(s):  
Irwin Guttman ◽  
Ulrich Menzefricke
Keyword(s):  
Response Surface ◽  
Surface Data

scholarly journals Complex Uncertainty of Surface Data Modeling via the Type-2 Fuzzy B-Spline Model

Mathematics ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1054
Author(s):  
Rozaimi Zakaria ◽  
Abd. Fatah Wahab ◽  
Isfarita Ismail ◽  
Mohammad Izat Emir Zulkifly
Keyword(s):  
Complex Surface ◽  
Complex Data ◽  
Fuzzy Data ◽  
Control Points ◽  
B Spline ◽  
Spline Surface ◽  
Data Control ◽  
Surface Data ◽  
Model Complex

This paper discusses the construction of a type-2 fuzzy B-spline model to model complex uncertainty of surface data. To construct this model, the type-2 fuzzy set theory, which includes type-2 fuzzy number concepts and type-2 fuzzy relation, is used to define the complex uncertainty of surface data in type-2 fuzzy data/control points. These type-2 fuzzy data/control points are blended with the B-spline surface function to produce the proposed model, which can be visualized and analyzed further. Various processes, namely fuzzification, type-reduction and defuzzification are defined to achieve a crisp, type-2 fuzzy B-spline surface, representing uncertainty complex surface data. This paper ends with a numerical example of terrain modeling, which shows the effectiveness of handling the uncertainty complex data.

scholarly journals Large-Scale and Deep-Seated Gravitational Slope Deformations on Mars: A Review

Geosciences ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 174
Author(s):  
Marco Emanuele Discenza ◽  
Carlo Esposito ◽  
Goro Komatsu ◽  
Enrico Miccadei
Keyword(s):  
Large Scale ◽  
High Quality ◽  
Surface Data ◽  
Geomorphological Processes ◽  
Gravitational Processes ◽  
Quality Surface ◽  
High Quality Surface ◽  
Mars Missions

The availability of high-quality surface data acquired by recent Mars missions and the development of increasingly accurate methods for analysis have made it possible to identify, describe, and analyze many geological and geomorphological processes previously unknown or unstudied on Mars. Among these, the slow and large-scale slope deformational phenomena, generally known as Deep-Seated Gravitational Slope Deformations (DSGSDs), are of particular interest. Since the early 2000s, several studies were conducted in order to identify and analyze Martian large-scale gravitational processes. Similar to what happens on Earth, these phenomena apparently occur in diverse morpho-structural conditions on Mars. Nevertheless, the difficulty of directly studying geological, structural, and geomorphological characteristics of the planet makes the analysis of these phenomena particularly complex, leaving numerous questions to be answered. This paper reports a synthesis of all the known studies conducted on large-scale deformational processes on Mars to date, in order to provide a complete and exhaustive picture of the phenomena. After the synthesis of the literature studies, the specific characteristics of the phenomena are analyzed, and the remaining main open issued are described.

Automated joint faulting measurement based on full-lane 3D pavement surface data

2021 ◽  
Vol 128 ◽  
pp. 103221
Author(s):  
Allen A. Zhang ◽  
Guangwei Yang ◽  
Kelvin C.P. Wang ◽  
Baoxian Li ◽  
Haiwang Kong ◽  
...  
Keyword(s):  
Pavement Surface ◽  
Surface Data

Parametrization of transition-metal Fermi-surface data

1975 ◽  
Vol 11 (4) ◽  
pp. 1447-1459 ◽  
Author(s):  
J. B. Ketterson ◽  
D. D. Koelling ◽  
J. C. Shaw ◽  
L. R. Windmiller
Keyword(s):  
Transition Metal ◽  
Fermi Surface ◽  
Surface Data

Frost risk mapping derived from satellite and surface data over the Bolivian Altiplano

1999 ◽  
Vol 95 (2) ◽  
pp. 113-137 ◽  
Author(s):  
C. François ◽  
R. Bosseno ◽  
J.J. Vacher ◽  
B. Seguin
Keyword(s):  
Risk Mapping ◽  
Frost Risk ◽  
Surface Data ◽  
Bolivian Altiplano
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