Spatial distribution and reserve estimation of sand and gravel deposits using geostatistical methods in west Basrah, southern Iraq


  • Safaa Al-Ali Department of Geology, College of Science, University of Basrah, Basrah, Iraq
  • Sattar Al-Khafaji Department of Geology, College of Science, University of Basrah, Basrah, Iraq


Sand and gravel are among the most common natural materials. They are generally used as a raw material in concrete, road construction, mixing with asphalt and filling material, among other uses. Sand and gravel deposits are widespread within the southern and central regions of Iraq. Among these deposits are the alluvial sand and gravel that form the upper part of the Dibdibba Formation in the Al-Rafiya, Al-Tuba, Chwaibda and Safwan blocks in west Basrah, southern Iraq. In this research, grain size distribution for channel samples collected from each block was determined. Thickness of overburden and industrial beds was measured and the stripping ratio (SR) was calculated. Geostatistical interpolation approaches including Inverse Distance Weighting (IDW) and ordinary kriging (OK) were utilised to predict the spatial distribution of sand and gravel deposits and their reserves from borehole data. Data validation using the mean error (ME) and root-mean-square error (RMSE) were applied. The deposits can be characterised as gravelly sand (gS) in the Al-Tuba, Al-Rafiya and Chwaibda blocks, while it is a sandy gravel (sG) in the Safwan block. The overburden gypcrete beds varied between 1−3 m thick, while the industrial sand and gravel beds which appear as planar and sometimes lenticular deposits ranging between 3−8 m thick. The SR is generally low, considering the easily removed lightweight material of the overburden bed and the easily extractable fairly flat and near-surface friable sand and gravel deposits. Reserves are estimated as 376.63 Million m3 and 385.97 Million m3 using the IDW and OK approaches, respectively. Based on the least error values of ME and RMSE, we conclude that the OK method is the more accurate spatial interpolation approach for sand and gravel reserve estimation in all blocks compared to the IDW method.





Earth & Environment