List of Articles

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  1 - Artificial Neural Networks Models for Rate of ‎Penetration Prediction in Rock Drilling‏ ‏
  naser ebadati Ronak Parvaneh Mehrab Azizi
  Based on field data, there are various methods to reduce the cost of drilling wells. One of these methods is to optimize the drilling parameters to obtain the maximum rate of penetration (ROP). Many parameters affect ROP. The main purpose of this research is the use of More

  Based on field data, there are various methods to reduce the cost of drilling wells. One of these methods is to optimize the drilling parameters to obtain the maximum rate of penetration (ROP). Many parameters affect ROP. The main purpose of this research is the use of smart networks for the penetration rate of drilling, for this purpose, well input data including drilling depth, duration of the drilling operation, speed of rotation of the drill, weight on the drill, weight and volume of drilling mud as input data. And the drilling penetration rate was prepared as output data from one of the fields located in the Persian Gulf. 70% of data is allocated for network training, 15% of data for validation and 15% of data for sensitivity analysis. According to the obtained results, it was found that using this tool, a good relationship with the total regression coefficient (0.96) is obtained for predicting the penetration rate using a neural network. Also, by repeating the calculations in repetition 12, the best value was obtained, which is equal to 14.24 Manuscript profile
• Open Access Article
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  2 - Assessing of heavymetals pollution in the agriculture soil ‎south of Bardaskan (Khorasan Razavi province)‎
  mohammad ebrahim fazel valipour
  Considering the development of industry and technology, the accumulation of inviromental contaminants,especially heavy metals in the soil led to increasing concern about food security.The aim of  this study was to investigate the concentration of heavy metals in th More

  Considering the development of industry and technology, the accumulation of inviromental contaminants,especially heavy metals in the soil led to increasing concern about food security.The aim of  this study was to investigate the concentration of heavy metals in the surface soils of agricultural lands south of Bardaskan located in Khorasan Razavi. The soil samples were taken from depth of 10 to 30 cm soil by filed assessment.The dominant soil texture is gravelsandy and PH 7.3 and subalkaline. Mean total concentration of Cd,Cu,Mn and Mo were0.66,251,2176,6.67(ppm).The highest values of Igeo,EF and CF indicators were found for Cu(0.6),Mo(6.26) ,Mo(4.44).Pollution index calculated using the average of total CF was 2.36,indicating the medium contamination class in the area. High concentration of heavy metals Cu,Mo,Mn and Cd in the south of Bardaskan can be a threat to agricultural land in this area. geological structures such as faults, and human activities such as mining, agriculture, and industry can provided the necessary grounds  for soil  contamination with heavy metals and increase the concentration of heavy metals in the agricultural soil of the region. Monitoring the pollutants concentration in the agricultural soils as well as in agriculutral products is essential to conserve natural resources and ensure the food security. Manuscript profile