The application of artificial neural networks for the prediction of water quality of polluted aquifer

Gumrah, F
Oz, B
Guler, B
Evin, S
From hydrocarbon reservoirs, beside of oil and natural gas, the brine is also produced as a waste material, which may be discharged at the surface or re-injected into the ground. When the wastewater is injected into the ground, it may be mixed with fresh water source due to to several reasons. Forecasting the pollutant concentrations by knowing the historical data at several locations on a field has a great importance to take the necessary precautions before the undesired situations are happened.


The use of genetic algorithms for determining the transport parameters of core experiments
Gumrah, F; Durgut, I; Oz, B; Yeten, B (2000-01-01)
From hydrocarbon reservoirs, brine is produced as a waste material, which may be injected into the ground or discharged at the surface. When the wastewater is injected into the ground, it may be mixed with fresh-water sources by several processes. Groundwater contamination from leakage, spills, or the injection of hazardous or toxic materials is widely regarded as one of the leading environmental problems. This study presents the use of genetic algorithms (GAs) as a viable means of estimating the transport ...
Optimal design and operation of land-treatment systems for petroleum hydrocarbons
Kivanc, S; Ünlü, Kahraman (1999-04-22)
Land treatment technology has been extensively used for the disposal of petroleum hydrocarbon containing wastes. Effective management of land treatment systems requires optimum design and operation of the system in order to achieve the fastest and most complete degradation of petroleum hydrocarbons without contamination of the environment. This paper describes a model that can be used for optimal design and operation of land treatment systems for petroleum hydrocarbon containing wastes. The model is compose...
An Experimental study on the effects of different chloride sources on the properties of API Class G cement
Ramazanoğlu, Özge; Yaman, İsmail Özgür; Akın, Serhat; Department of Cement Engineering (2014)
In the petroleum industry, oil well cements are used in the form of slurries during the construction of oil or natural gas wells. Preserving the integrity of the well and the casing, providing zonal isolation are some of the uses of these special cements. Oil well cement slurries used in the petroleum industry are subjected to different exposure conditions than ordinary Portland cement slurries used in the construction industry. Therefore, oil well cements are required to possess different engineering prope...
The use of fractal geostatistics and artificial neural networks for carbonate reservoir characterization
Yeten, B; Gumrah, F (2000-11-01)
In this study, a carbonate oil reservoir located in the southeast part of Turkey was characterized by the use of kriging and the fractal geometry. The three-dimensional porosity and permeability distributions were generated by both aforementioned methods by using the wireline porosity logs and core plug permeability measurements taken from six wells of the field. Since classical regression (lognormal or polynomial) and geostatistical techniques (cross variograms) fail to estimate permeability from wireline ...
A study of thin film solid phase microextraction methods for analysis of fluorinated benzoic acids in seawater
Boyacı, Ezel; Viteri, C. Ricardo; Pawliszyn, Janusz (2016-03-04)
Fluorinated benzoic acids (FBAs) are frequently used as tracers by the oil industry to characterize petroleum reservoirs. The demand for fast, reliable, robust, and sensitive approaches to separate and quantify FBAs in produced water, both in laboratory and field conditions, has not been yet fully satisfied. In this study, for the first time, thin film solid phase microextraction (TF-SPME) is proposed as a versatile sample preparation tool for the determination of FBAs in produced water by pursing two diffe...
Citation Formats
F. Gumrah, B. Oz, B. Guler, and S. Evin, “The application of artificial neural networks for the prediction of water quality of polluted aquifer,” WATER AIR AND SOIL POLLUTION, pp. 275–294, 2000, Accessed: 00, 2020. [Online]. Available: