804085 Method for determination of anisotropic coefficients of permeability and specific storage from pumping test data storage from pumping test data

Seventeen Schlumberger vertical electrical soundings (VES) were carried out in parts of the Umuahia area of Nigeria, using a maximum current electrode separation of 1 km. The data were interpreted using a conventional partial curve‐matching method to obtain initial model parameters, which were used in a computer program to obtain final parameters. Three soundings were made at existing boreholes for comparison. Aquifer parameters of hydraulic conductivity and transmissivity were obtained by analyzing pumping test data from existing boreholes. The results of the interpretation revealed three distinct geoelectric layers overlying a conductive geoelectric basement. Based on the model obtained, aquifer hydraulic conductivity and transmissivity were calculated. The hydraulic conductivity calculated agreed closely with that determined from pumping test data. The results of the present study also indicate that the entire area is divided into two zones, each of which is homogeneous in hydraulic properties and water quality, but distinct from the other zone. A local groundwater divide between the Imo and Kwa‐Ibo drainage systems was also defined.

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Determination of aquifer parameters using geoelectrical sounding and pumping test data in Khanewal District, Pakistan

Open Geosciences ◽

10.1515/geo-2016-0071 ◽

2016 ◽

Vol 8 (1) ◽

Cited By ~ 17

Author(s):

Gulraiz Akhter ◽

M. Hasan

Keyword(s):

Test Data ◽

Groundwater Resources ◽

Pumping Test ◽

Vertical Electrical Sounding ◽

Analytical Relationship ◽

Pumping Tests ◽

Aquifer Parameters ◽

Surface Measurements ◽

Electrical Sounding

AbstractIn order to determine the groundwater resources and potentials of the Khanewal District of Pakistan, a geophysical method in combination with pumping test data were used. An analytical relationship between the aquifer parameters interpreted from surface geoelectrical method and pumping test was established in order to estimate aquifer parameters from surface measurements where no pumping tests exist. For the said purpose, 48 geoelectric investigations were carried out using Schlumberger vertical electrical sounding (VES). Seven of the soundings were conducted where pumping tests had been carried out at borehole sites. The vertical electrical sounding stations were interpreted, and resistivities and thickness parameters were calculated. The values of transmissivity and hydraulic conductivity were calculated using the Dar Zarrouk parameter. Transmissivity values obtained from pumping test data and the VES method range between 954 – 4263 m

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Research on a Method of an Automatic Determination of Aquifer Coefficients from Pumping Test Data

SOILS AND FOUNDATIONS ◽

10.3208/sandf1972.23.4_178 ◽

1983 ◽

Vol 23 (4) ◽

pp. 178-184

Author(s):

Makoto Nishigaki

Keyword(s):

Test Data ◽

Pumping Test ◽

Automatic Determination

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An Innovative Approach to Determination of Double-Porosity Fractured Aquifers Hydraulic Parameters Using Artificial Neural Network

10.21203/rs.3.rs-587986/v1 ◽

2021 ◽

Author(s):

Tahereh Azari ◽

Mahmoud Mohammad Rezapour Tabari

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Test Data ◽

Pumping Test ◽

Double Porosity ◽

Aquifer Parameters ◽

Aquifer Parameter ◽

Well Function ◽

Parameter Values

Abstract Accurate determination of hydraulic parameter values is the first step to the sustainable development of an aquifer. Since Theis (1935), type curve matching technique (TCMT) has been used to estimate the aquifer parameters from pumping test data. The TCMT is subjected to graphical error. To eliminate the error an Artificial Neural Network (ANN) is developed as an alternative to the conventional TCMT by modeling the Bourdet-Gringaten’s well function for the determination of the fractured double porosity aquifer parameters. The neural network model is developed in a six-step protocol based on multi-layer perceptron (MLP) networks architecture and is trained for the well function of double porosity aquifers by the back propagation method and the Levenberg-Marquardt optimization algorithm. By applying the principal component analysis on the training input data and through a trial-and-error procedure the optimum structure of the network is fixed with the topology of [3×6×3]. The replicative, predictive and structural validity of the developed network are evaluated with synthetic and real field data. The developed network provides an automatic and fast procedure for the double porosity aquifer parameter determination that eliminates graphical errors inherent in the conventional TCMT. The network receives pumping test data and provides the user with the aquifer parameter values.

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