TY - THES

T1 - Formation Breakdown Pressure Prediction Models and Their Applicability in Various Rock Types and Wellbores

AU - Kiss, Akos

N1 - embargoed until 10-11-2020

PY - 2015

Y1 - 2015

N2 - The thesis describes the comparison of predicted Formation Breakdown Pressures (FBP) calculated from industry wide accepted models to actual measured pressure values. Data from 141 hydraulic fracturing treatments were evaluated coming from different gas and oil fields of OMV Aktiengesellschaft and Devon Energy Corporation. The aim of the thesis work was to investigate the accuracy and validity of the various models in a holistic approach examining formations covering a wide range of different sandstone formations, some fields with carbonate formation and one shale gas play. Therefore the calculated and measured bottomhole FBP values range from weak to strong formations with FBP’s from 4333 psi to 16707 psi. All employed models are published and described in detail in technical papers and classified as elastic, linear elastic, poroelastic, linear elastic fracture mechanics, point stress and thermoporoelastic models. The correlations were compared using an error analysis framework and their accuracy and precision was identified. Six error analysis parameters were determined and by using them a ranking mechanism was established. Followed by a sensitivity analysis of the input parameters for the most accurate model. Based on this sensitivity analysis the principal rock parameters which influence most the accuracy of FBP prediction were identified. Since the results of the study did not allow individuating an easy and consistent prediction model which is valid for all investigated formations, one of the commercially available artificial neural network software was tested, if it is capable to provide accurate FBP prediction for all types of reservoir formations. This approach, where information technology is combined with petroleum engineering, is an emerging technology and interpretation technique in the oil and gas industry. The validity of this method has been proven by predicting the Formation Breakdown Pressure with reasonable low error margins of

AB - The thesis describes the comparison of predicted Formation Breakdown Pressures (FBP) calculated from industry wide accepted models to actual measured pressure values. Data from 141 hydraulic fracturing treatments were evaluated coming from different gas and oil fields of OMV Aktiengesellschaft and Devon Energy Corporation. The aim of the thesis work was to investigate the accuracy and validity of the various models in a holistic approach examining formations covering a wide range of different sandstone formations, some fields with carbonate formation and one shale gas play. Therefore the calculated and measured bottomhole FBP values range from weak to strong formations with FBP’s from 4333 psi to 16707 psi. All employed models are published and described in detail in technical papers and classified as elastic, linear elastic, poroelastic, linear elastic fracture mechanics, point stress and thermoporoelastic models. The correlations were compared using an error analysis framework and their accuracy and precision was identified. Six error analysis parameters were determined and by using them a ranking mechanism was established. Followed by a sensitivity analysis of the input parameters for the most accurate model. Based on this sensitivity analysis the principal rock parameters which influence most the accuracy of FBP prediction were identified. Since the results of the study did not allow individuating an easy and consistent prediction model which is valid for all investigated formations, one of the commercially available artificial neural network software was tested, if it is capable to provide accurate FBP prediction for all types of reservoir formations. This approach, where information technology is combined with petroleum engineering, is an emerging technology and interpretation technique in the oil and gas industry. The validity of this method has been proven by predicting the Formation Breakdown Pressure with reasonable low error margins of

KW - hydraulic fracturing

KW - formation breakdown pressure

KW - artificial neural networks

KW - hydraulic fracturing

KW - formation breakdown pressure

KW - neuronalen netzwerk

M3 - Master's Thesis

ER -