Oil and natural gas production has been an important economic booster in the recent past. However, unconventional methods have risen environmental health concerns. This study presents preliminary results of heavy metal concentrations in water (surface and groundwater) samples around oil and natural gas drilling sites in East-West Godavari districts of A.P, India. A total of 36 samples, 24 surface water (SW) and 12 groundwater (GW) were collected to evaluate the distribution of pH, EC, TDS, As,

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... d, Cr, Cu, Mo, Ni, Pb, Zn, and radiogenic elements (U, Th). Results acquired were treated with principal component analysis (PCA)/factor analysis (FA), hierarchical cluster analysis (HCA), and regression coefficient analysis to identify a collective contamination source. Mean concentrations obtained for surface and groundwater were 7.60 and 7.34 for pH; 4048 and 2964 mg/L for TDS; 8.50 and 5.91 µs/cm for EC; 11.5 and 10.7 μg/L for As; 14.6 and 10.8 μg/L for Cr; 0.60 and 0.70 μg/L for Cd; 18.6 and 29.1 μg/L for Cu; 3.00 and 4.20 μg/L for Mo; 19.9 and 24.8 for Ni; 15.2 and 13.4 μg/L for Pb; 4.60 and 3.10 μg/L for Th; 1.00 and 8.30 μg/L for U; 187 and 348 μg/L for Zn respectively. FA recognized four factors accountable for data structure elucidating 86.23 % of the total variance in SW, four factors in GW explaining 91.6%, and permitted to assemble particular parameters based on collective features. As, Cd, Cu, Mo, Pb, and U were linked and well-ordered by diverse origin with related influence from anthropogenic and geogenic sources. This study describes the importance and efficacy of multivariate statistical methods for evaluation and understanding the data to get better evidence about the water quality and project some mitigation methods to avert the contamination affected by harmful heavy metals in the future.