In heterogeneous tight sand formations, horizontal wells encounter intervals deposited under varying depositional environments along the lateral portion of the wellbore between landing point and total depth. Horizontal wells in this study were drilled in tight sands deposited in a marine environment where lateral depositional facies changes are common, and hydraulic fracture stimulation is necessary to achieve economic hydrocarbon extraction due to the relatively low permeability of the formation. Without geomechanical logs currently derived from wireline logging, it is not possible to optimize cluster spacing and placement. This step provides necesary information used to optimize completion design, which is crucial to the ultimate productivity of a well. Due to formation heterogeneity, expensive wireline logs must be collected in order to optimize fracture stimulation or else new methods to estimate these logs must be employed. This paper presents a technique to optimize cluster selection for hydraulic fracturing in unconventional tight gas development horizontal wells without wireline logging by leveraging Measure While Drilling (MWD) Gamma Ray logs and surface drilling parameters together with Artificial Intelegence (AI) algorythms to predict density, compressional and shear slowness logs for use in geomechanical evaluation.
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