Fig 1.
The process of marking directional resistivity for core samples.
(A) This figure illustrates the first procure, which involves dividing the cylindrical rock core into equidistant segments and conducting resistivity tests on each segment. (B) This figure presents the second procure, in which positions with multiple maximum resistivity values are labeled. (C) This figure depicts the scenario where all data points fall within one complete cycle relative to the origin point “O”. (D) This figure explains the scenario in which multiple peak segments occur, with the latter segment just crossing the origin “O,” resulting in an “overlapping loop” condition.
Fig 2.
The process of marking directional resistivity for electrical imaging logging.
(A) This figure illustrates the third procure, which involves dividing the resistivity image into equidistant segments and then calculating the respective resistivity values. (B) This figure explains the fourth step, labeling positions with multiple maximum resistivity values on the resistivity image. (C) This figure depicts the scenario on the resistivity image where all points fall within a single cycle. (D) This figure describes the situation on the resistivity image where two peak segments occur, with the latter segment resulting in an “overlapping loop” condition.
Fig 3.
Resistivity distribution of sample 159 from well ST12.
From the test data, it can be observed that at different water saturation levels, the resistivity of the rock core still exhibits some variation along different directions.
Fig 4.
Directional conductivity of core sample 159 from well ST12 correlated with electrical imaging.
This figure illustrates the process of comparing the radial resistivity test values of a cylindrical rock core with electrical imaging logging data to determine the original orientation of the core in the formation.
Table 1.
Comparison of different core orientation techniques.
Fig 5.
Original formation orientation readings mapped on the electrical imaging log.
This figure demonstrates how the brightest and darkest values are obtained by extracting data from point imaging logging images.