Integration of geologic, geochemical, and geophysical data of the Cement oil field, Oklahoma, using spatial array processing

Geophysics ◽  
1983 ◽  
Vol 48 (10) ◽  
pp. 1305-1317 ◽  
Author(s):  
Patricia Termain Eliason ◽  
Terrence J. Donovan ◽  
Pat S. Chavez
Keyword(s):  
Gamma Ray ◽  
Array Processing ◽  
Data Interpretation ◽  
Test Site ◽  
Oil Field ◽  
Pictorial Representation ◽  
Gamma Ray Spectrometry ◽  
Rectangular Array ◽  
Data Set ◽  
Contour Maps

Geologic, geochemical, and geophysical measurements were made at the Cement oil field, Oklahoma, test site using airborne and spaceborne sensors coupled with ground‐based data collection. The data collected include (1) airborne gamma‐ray spectrometry ([Formula: see text], [Formula: see text], [Formula: see text], and total intensity channels), (2) low‐altitude aeromagnetic profiles, (3) precision gravity measurements, (4) images from the Landsat multispectral scanner (MSS) systems and U-2 photography, and (5) geologic and topographic maps. In order to reduce, analyze, display, and correlate the information, it was necessary to transform the data from vector space to raster space (a two‐dimensional image array) with fixed resolution and array dimension. With the data in array form, spatial array processing techniques were applied to (1) correct geometrically the data for proper registration, (2) perform areal interpolation and smoothing, (3) display the data as images, and (4) perform integration and correlation studies. Each data set was transformed into a rectangular array covering approximately 0.3 degrees of latitude and longitude, with each picture element encompassing [Formula: see text]. Because most variables only sparsely populate the raw image array (i.e., flight line data), the data were interpolated and smoothed using spatial filtering techniques to construct continuous images. The individual data sets were displayed as black and white continuous tone images, color coded to form color contour maps, or manipulated to generate shaded‐relief models. Methods for correlation and data interpretation were systematically investigated by using all available sources. Predetermined factual information (“prior knowledge” correlation statistics) was used to establish grounds for correlation and better define the limits of the data. This kind of data manipulation provided an enhanced pictorial representation of the geologic, geochemical, and geophysical anomalies previously documented at Cement.

Imaging of an active fault: Comparison between 3D GPR data and outcrops at the Castrovillari fault, Calabria, Italy

2015 ◽  
Vol 3 (3) ◽  
pp. SY57-SY66 ◽  
Author(s):  
Ercoli Maurizio ◽  
Pauselli Cristina ◽  
Romana Cinti Francesca ◽  
Forte Emanuele ◽  
Volpe Roberto
Keyword(s):  
Active Fault ◽  
Data Interpretation ◽  
Test Site ◽  
Quantitative Information ◽  
Data Set ◽  
Strong Earthquakes ◽  
The Past ◽  
3D Gpr ◽  
Dip Angle ◽  
Ground Penetrating

We have integrated and analyzed a 3D ground-penetrating radar (GPR) volume with a trenching exposure data set to evaluate the potential of these methods individually and combined for study of a fault zone. We chose a test site across a branch of the active Castrovillari fault in the Northern Calabria (Southern Italy). This tectonic structure is one of the most active in the area, and it has generated strong earthquakes in the past. Based on analysis of previously collected data, a 3D GPR survey was carried out 1.2 m from a fault outcrop. The goal was to use the GPR volume to guide and optimize the excavation of a trench and then to use the trenching data to validate the GPR volume interpretation. We used seismic interpretation software to display vertical and horizontal sections and for horizon tracking and attribute analyses. We obtained quantitative information on the geometry of structural and geologic features, such as fault strike and dip angle, defining the boundaries of different stratigraphic units. We validated our GPR data interpretation with the outcrop section and trench wall demonstrating the benefits of GPR in extensional tectonics environments and the great potential of the combined geologic and geophysical approach.

scholarly journals Analysis of permeability based on petrophysical logs: comparison between heuristic numerical and analytical methods

2021 ◽  
Vol 11 (5) ◽  
pp. 2097-2111
Author(s):  
H. Heydari Gholanlo
Keyword(s):  
Gamma Ray ◽  
Search Algorithm ◽  
Harmony Search ◽  
Harmony Search Algorithm ◽  
Oil Field ◽  
Reservoir Properties ◽  
Model Learning ◽  
K Nearest Neighbors ◽  
Data Set ◽  
Petrophysical Logs

AbstractA series of novel heuristic numerical tools were adopted to tackle the setback of permeability estimation in carbonate reservoirs compared to the classical methods. To that end, a comprehensive data set of petrophysical data including core and log in two wells was situated in Marun Oil Field. Both wells, Well#1 and Well#2, were completed in the Bangestan reservoir, having a broad diversity of carbonate facies. In the light of high Lorenz coefficients, 0.762 and 0.75 in Well#1 and Well#2, respectively, an extensive heterogeneity has been expected in reservoir properties, namely permeability. Despite Well#1, Well#2 was used as a blinded well, which had no influence on model learning and just contributed to assess the validation of the proposed model. An HFU model with the aim of discerning the sophistication of permeability and net porosity interrelation has been developed in the framework of Amaefule’s technique which has been modified by newly introduced classification and clustering conceptions. Eventually, seven distinct pore geometrical units have been distinguished through implementing the hybridized genetic algorithm and k-means algorithm. Furthermore, a K-nearest neighbors (KNN) algorithm has been carried out to divide log data into the flow units and assigns them to the pre-identified FZI values. Besides, a cross between the ε-SVR model, a supervised learning machine, and the Harmony Search algorithm has been used to estimate directly permeability. To select the optimum combination of the involved logging parameters in the ε-SVR model and reduce the dimensionality problem, a principle component analysis (PCA) has been implemented on Well#1 data set. The result of PCA illustrates parameters, such as permeability, the transit time of sonic wave, resistivity of the unflashed zone, neutron porosity, photoelectric index, spectral gamma-ray, and bulk density, which possess the highest correlation coefficient with first derived PC. In line with previous studies, the findings will be compared with empirical methods, Coates–Dumanior, and Timur methods, which both have been launched into these wells. Overall, it is obvious to conclude that the ε -SVR model is undeniably the superior method with the lowest mean square error, nearly 4.91, and the highest R-squared of approximately 0.721. On the contrary, the transform relationship of porosity and permeability has remarkably the worst results in comparison with other models in error (MSE) and accuracy (R2) of 128.73 and 0.116, respectively.

Gamma-Ray Spectrometric Analysis of Some Trace Elements in the Human Articular Disc of the Mandible

1963 ◽  
Vol 03 (02) ◽  
pp. 175-182 ◽  
Author(s):  
Bo Bergman ◽  
Rune Söremark
Keyword(s):  
Trace Elements ◽  
Neutron Activation ◽  
Quantitative Data ◽  
Thermal Neutron Flux ◽  
Gamma Ray ◽  
Dry Weight ◽  
Gamma Ray Spectrometry ◽  
Spectrometric Analysis ◽  
Articular Disc ◽  
Group Separation

SummaryBy means of neutron activation and gamma-ray spectrometry the concentrations in the human mandibular articular disc of the following elements have been determined: Na, Mn, Cu, Zn, Rb, Sr, Cd, W, and Au. The discs were obtained at necropsy from seven men and nine women, ranging in age from 56 to 71 years.The activation was carried out in a thermal neutron flux of about 1.7 XlO12 neutrons × cm−2 × sec.−1 for about 20 hours. A chemical group separationwas performed before the gamma-ray spectrometry. Quantitative data based on the dry weight of the cartilage samples were obtained by comparing the photo-peak area of the identified elements with those of appropriate standards.

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