A fast interpretation of self-potential data using the depth from extreme points method

Geophysics ◽  
2013 ◽  
Vol 78 (2) ◽  
pp. E107-E116 ◽  
Author(s):  
Maurizio Fedi ◽  
Mahmoud Ahmed Abbas
Keyword(s):  
Scaling Law ◽  
Extreme Points ◽  
Real Data ◽  
High Order ◽  
The Self ◽  
Source Distribution ◽  
Imaging Method ◽  
Fast Method ◽  
Structural Index ◽  
Self Potential

We used a fast method to interpret self-potential data: the depth from extreme points (DEXP) method. This is an imaging method transforming self-potential data, or their derivatives, into a quantity proportional to the source distribution. It is based on upward continuing of the field to a number of altitudes and then multiplying the continued data with a scaling law of those altitudes. The scaling law is in the form of a power law of the altitudes, with an exponent equal to half of the structural index, a source parameter related to the type of source. The method is autoconsistent because the structural index is basically determined by analyzing the scaling function, which is defined as the derivative of the logarithm of the self-potential (or of its [Formula: see text]th derivative) with respect to the logarithm of the altitudes. So, the DEXP method does not need a priori information on the self-potential sources and yields effective information about their depth and shape/typology. Important features of the DEXP method are its high-resolution power and stability, resulting from the combined effect of a stable operator (upward continuation) and a high-order differentiation operator. We tested how to estimate the depth to the source in two ways: (1) at the positions of the extreme points in the DEXP transformed map and (2) at the intersection of the lines of the absolute values of the potential or of its derivative (geometrical method). The method was demonstrated using synthetic data of isolated sources and using a multisource model. The method is particularly suited to handle noisy data, because it is stable even using high-order derivatives of the self-potential. We discussed some real data sets: Malachite Mine, Colorado (USA), the Sariyer area (Turkey), and the Bender area (India). The estimated depths and structural indices agree well with the known information.

DEXP: A fast method to determine the depth and the structural index of potential fields sources

Geophysics ◽  
2007 ◽  
Vol 72 (1) ◽  
pp. I1-I11 ◽  
Author(s):  
Maurizio Fedi
Keyword(s):  
Potential Field ◽  
Extreme Points ◽  
Power Laws ◽  
Potential Fields ◽  
Newtonian Potential ◽  
Specific Power ◽  
Scaling Exponent ◽  
Fast Method ◽  
Structural Index ◽  
Derivatives Of

We show that potential fields enjoy valuable properties when they are scaled by specific power laws of the altitude. We describe the theory for the gravity field, the magnetic field, and their derivatives of any order and propose a method, called here Depth from Extreme Points (DEXP), to interpret any potential field. The DEXP method allows estimates of source depths, density, and structural index from the extreme points of a 3D field scaled according to specific power laws of the altitude. Depths to sources are obtained from the position of the extreme points of the scaled field, and the excess mass (or dipole moment) is obtained from the scaled field values. Although the scaling laws are theoretically derived for sources such as poles, dipoles, lines of poles, and lines of dipoles, we give also criteria to estimate the correct scaling law directly from the data. The scaling exponent of such laws is shown to be related to the structural index involved in Euler Deconvolution theory. The method is fast and stable because it takes advantage of the regular behavior of potential field data versus the altitude [Formula: see text]. As a result of stability, the DEXP method may be applied to anomalies with rather low SNRs. Also stable are DEXP applications to vertical and horizontal derivatives of a Newtonian potential of various orders in which we use theoretically determined scaling functions for each order of a derivative. This helps to reduce mutual interference effects and to obtain meaningful representations of the distribution of sources versus depth, with no prefiltering. The DEXP method does not require that magnetic anomalies to be reduced to the pole, and meaningful results are obtained by processing its analytical signal. Application to different cases of either synthetic or real data shows its applicability to any type of potential field investigation, including geological, petroleum, mining, archeological, and environmental studies.

scholarly journals Distinguishing linear and branched evolution given single-cell DNA sequencing data of tumors

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Leah L. Weber ◽  
Mohammed El-Kebir
Keyword(s):  
Dna Sequencing ◽  
Single Cell ◽  
Evolutionary Process ◽  
Treatment Decision ◽  
Real Data ◽  
Current Data ◽  
Fast Method ◽  
Sequencing Data ◽  
Evolutionary Trajectory ◽  
Cancer Types

Abstract Background Cancer arises from an evolutionary process where somatic mutations give rise to clonal expansions. Reconstructing this evolutionary process is useful for treatment decision-making as well as understanding evolutionary patterns across patients and cancer types. In particular, classifying a tumor’s evolutionary process as either linear or branched and understanding what cancer types and which patients have each of these trajectories could provide useful insights for both clinicians and researchers. While comprehensive cancer phylogeny inference from single-cell DNA sequencing data is challenging due to limitations with current sequencing technology and the complexity of the resulting problem, current data might provide sufficient signal to accurately classify a tumor’s evolutionary history as either linear or branched. Results We introduce the Linear Perfect Phylogeny Flipping (LPPF) problem as a means of testing two alternative hypotheses for the pattern of evolution, which we prove to be NP-hard. We develop Phyolin, which uses constraint programming to solve the LPPF problem. Through both in silico experiments and real data application, we demonstrate the performance of our method, outperforming a competing machine learning approach. Conclusion Phyolin is an accurate, easy to use and fast method for classifying an evolutionary trajectory as linear or branched given a tumor’s single-cell DNA sequencing data.

scholarly journals Mapping the Pollution Plume Using the Self-Potential Geophysical Method: Case of Oum Azza Landfill, Rabat, Morocco

Water ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 961
Author(s):  
Meryem Touzani ◽  
Ismail Mohsine ◽  
Jamila Ouardi ◽  
Ilias Kacimi ◽  
Moad Morarech ◽  
...  
Keyword(s):  
Electrical Conductivity ◽  
Water Table ◽  
Soil Surface ◽  
The Self ◽  
Drainage Network ◽  
Geophysical Method ◽  
Direct Measurements ◽  
Sandy Material ◽  
The City ◽  
Self Potential

The main landfill in the city of Rabat (Morocco) is based on sandy material containing the shallow Mio-Pliocene aquifer. The presence of a pollution plume is likely, but its extent is not known. Measurements of spontaneous potential (SP) from the soil surface were cross-referenced with direct measurements of the water table and leachates (pH, redox potential, electrical conductivity) according to the available accesses, as well as with an analysis of the landscape and the water table flows. With a few precautions during data acquisition on this resistive terrain, the results made it possible to separate the electrokinetic (~30%) and electrochemical (~70%) components responsible for the range of potentials observed (70 mV). The plume is detected in the hydrogeological downstream of the discharge, but is captured by the natural drainage network and does not extend further under the hills.

scholarly journals A Community-Structure-Based Method for Estimating the Fractal Dimension, and its Application to Water Networks for the Assessment of Vulnerability to Disasters

2021 ◽  
Vol 35 (4) ◽  
pp. 1197-1210
Author(s):  
C. Giudicianni ◽  
A. Di Nardo ◽  
R. Greco ◽  
A. Scala
Keyword(s):  
Fractal Dimension ◽  
Community Structure ◽  
Distribution Systems ◽  
Water Distribution ◽  
Scaling Law ◽  
Vulnerability Index ◽  
The Self ◽  
Node Degree ◽  
Specific Response ◽  
Self Similarity

AbstractMost real-world networks, from the World-Wide-Web to biological systems, are known to have common structural properties. A remarkable point is fractality, which suggests the self-similarity across scales of the network structure of these complex systems. Managing the computational complexity for detecting the self-similarity of big-sized systems represents a crucial problem. In this paper, a novel algorithm for revealing the fractality, that exploits the community structure principle, is proposed and then applied to several water distribution systems (WDSs) of different size, unveiling a self-similar feature of their layouts. A scaling-law relationship, linking the number of clusters necessary for covering the network and their average size is defined, the exponent of which represents the fractal dimension. The self-similarity is then investigated as a proxy of recurrent and specific response to multiple random pipe failures – like during natural disasters – pointing out a specific global vulnerability for each WDS. A novel vulnerability index, called Cut-Vulnerability is introduced as the ratio between the fractal dimension and the average node degree, and its relationships with the number of randomly removed pipes necessary to disconnect the network and with some topological metrics are investigated. The analysis shows the effectiveness of the novel index in describing the global vulnerability of WDSs.

Experimental study of the self-potential anomaly caused by coal fires

2017 ◽  
Vol 145 ◽  
pp. 124-132 ◽  
Author(s):  
Zhenlu Shao ◽  
Deming Wang ◽  
Yanming Wang ◽  
Xiaoxing Zhong ◽  
Yunxiang Zhang ◽  
...  
Keyword(s):  
Experimental Study ◽  
The Self ◽  
Coal Fires ◽  
Self Potential

Mapping Fracture Flow Anisotropy Using the Self Potential Method: Field and Laboratory Experiments

2021 ◽  
Author(s):  
Y. Kumar ◽  
J. Comte ◽  
J. Vinogradov ◽  
D. Healy ◽  
J. Mezquita Gonzalez ◽  
...  
Keyword(s):  
Laboratory Experiments ◽  
Potential Method ◽  
The Self ◽  
Fracture Flow ◽  
Self Potential ◽  
Flow Anisotropy

The emergence of high-order systems of the self

2018 ◽  
pp. 60-63
Author(s):  
Dorothy Heard ◽  
Brian Lake
Keyword(s):  
High Order ◽  
The Self

scholarly journals Self-potential response characteristics of red sandstone samples under uniaxial compression

2019 ◽  
Vol 16 (4) ◽  
pp. 742-752
Author(s):  
Cai Yang ◽  
Shengdong Liu ◽  
Haiping Yang
Keyword(s):  
Rock Mass ◽  
Uniaxial Compression ◽  
Inflection Point ◽  
Radial Direction ◽  
The Self ◽  
Potential Difference ◽  
Potential Response ◽  
Red Sandstone ◽  
Response Characteristics ◽  
Self Potential

Abstract Deformation and rupture of rock mass under loading cause the variation of electric potential. Response characteristics of self-potential and stress during the complete stress-strain process of red sandstones play an important role in evaluating the stress state of sandstone on the basis of self-potential. Experimental results demonstrate that the stress of red sandstone under uniaxial compression is linearly correlated with the self-potential difference before the first inflection point in the initial stage of loading. The average variation rate of self-potential difference and stress is 0.1325 mV MPa−1. As the loading pressure gradually increases and enters the softening stage (before the maximum loading point), the catastrophic points of uniaxial loading stress correspond to the inflection point of self-potential. The self-potential of red sandstone varies in a range of 0–45.6 mV in that case and it fluctuates most significantly around the maximum loading point, with a range of 0.3–195.5 mV. In the end stage of loading, the macroscopic rupture of the red sandstone sample is complete, the self-potential of red sandstone fluctuates slightly around the maximum load point and then gradually stabilizes. Moreover, it is found that self-potentials change more significantly in the radial direction than in the axial direction in the uniaxial compression experiment, indicating that self-potentials generated by rock mass rupture are more sensitive in the radial direction. The rupture process of red sandstone can be dynamically represented by the tempo-spatial evolution profiles of self-potential.

Sign in / Sign up

Export Citation Format

Share Document