Optimization of hydraulic fracturing procedure in the exploration of shale gas type reserves
Thayna Cardoso Gonçalves1; Juliana Souza Baioco2; Beatriz Souza Leite Pires de Lima1; Breno Pinheiro Jacob1
1 LAMCSO/ PEC/COPPE/UFRJ; 2 LAMCSO/ PEC/COPPE/UFRJ and TEQ/UFF
doi:10.20906/CPS/CILAMCE2017-0129
Resumo
Hydraulic fracturing (HF) is a well-stimulation technique aiming mainly to increase productivity by establishing highly conductive structures in the formation, the fractures. HF has become the technology that allows the development of unconventional reservoirs. Tight gas, shale oil, shale gas and coalbed methane, for example, are resources dependent on hydraulic fracturing for its commercial viability. Several unconventional basins were in the 12th Bidding Round from the National Agency of Petroleum, Gas and Biofuels (ANP), therefore, this research project focuses on a study regarding this reservoir types. For that reason,this research is very relevant to the upcoming scenario. This research intends to study the manner on which some variables of hydraulic fracturing impact the well productivity and develop an optimization tool based on evolutionary algorithms intending to find an optimal solution for reaching the maximum well productivity through the parameters that are part of the process, such as porosity and permeability of the proppant pack. For that, the Unified Fracture Design will be used to evaluatethe hydraulic fracturing in a case study. The outcomes will be the proppant number, optimal conductivity, widthand length of the fracture, optimal productivity index of the fractured well, skin factor and the folds of increase factor. Ultimately, the results generated by the Unified Fracturing Design will be compared to the ones generated by the evolving algorithms. Among the outcomes, the most interesting ones for reaching the optimal result will be Fold of Increase, the productivity index and the skin factor.The first two are expected to increase and the third is expected to decrease when set side to side with the results used as basis.
Palavras-chave: Hydraulic Fracturing ; Optimization; Genetic Algorithms; Petroleum