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QGIS well log and timeseries visualisation plugin Oslandia, Orano and CEA: GPLv2 or later: Cross-platform: Python: Interfaces with QGIS: OpenGeoPlotter Mineral exploration drill hole data visualization and cross section generator, strip logs, stereonet GPL: Cross-platform: Python: Open source PyQt5 app catered to the exploration industry
Well logging, also known as borehole logging is the practice of making a detailed record (a well log) of the geologic formations penetrated by a borehole.The log may be based either on visual inspection of samples brought to the surface (geological logs) or on physical measurements made by instruments lowered into the hole (geophysical logs).
A drilling rig is used to create a borehole or well (also called a wellbore) in the earth's sub-surface, for example in order to extract natural resources such as gas or oil. During such drilling, data is acquired from the drilling rig sensors for a range of purposes such as: decision-support to monitor and manage the smooth operation of ...
Well to well correlation: gamma-ray log fluctuates with changes in formation mineralogy. As such, gamma-ray logs from different wells within the same field or region can be very useful for correlation purposes, because similar formations show similar features.
Density logging is a well logging tool that can provide a continuous record of a formation's bulk density along the length of a borehole.In geology, bulk density is a function of the density of the minerals forming a rock (i.e. matrix) and the fluid enclosed in the pore spaces.
Spontaneous potential log, commonly called the self potential log or SP log, is a passive measurement taken by oil industry well loggers to characterise rock formation properties. The log works by measuring small electric potentials (measured in millivolts) between depths with in the borehole and a grounded electrode at the surface.
A log–log plot of y = x (blue), y = x 2 (green), and y = x 3 (red). Note the logarithmic scale markings on each of the axes, and that the log x and log y axes (where the logarithms are 0) are where x and y themselves are 1. Comparison of linear, concave, and convex functions when plotted using a linear scale (left) or a log scale (right).
In the analysis of data, a correlogram is a chart of correlation statistics. For example, in time series analysis, a plot of the sample autocorrelations versus (the time lags) is an autocorrelogram. If cross-correlation is plotted, the result is called a cross-correlogram.