A New Analytical Model to Evaluate Uncertainty of Wellbore Collapse Pressure Based on Advantageous Synergies of Different Strength Criteria

Zhang, Lisong; Bian, Yinghui; Zhang, Shiyan; Yan, Yifei

doi:10.1007/s00603-018-1729-1

Cited by 7 publications

(9 citation statements)

References 40 publications

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“…New CPM Based on the Advantageous Synergy among Different Criteria. Different criteria have been developed or employed to conduct WSA, but the collapse pressure does not comply with different strength criteria, and some of the authors indicated that the best strength criteria are different for various well trajectories under different stress regimes [52,53]. Zhang et al [53] integrated the advantageous synergy among the M-C, D-P, ML, and Mg-C criteria to propose a new CPM of vertical wells, the advantageous synergy among different strength criteria assumes that each strength criterion has a different weight coefficient, and the real collapse pressure should be determined by combining both conventional CPMs and their corresponding weight coefficient.…”

Section: Geofluidsmentioning

confidence: 99%

“…Due to the introduction of weight coefficients, this new analytical model of collapse pressure of inclined wellbore can involve the advantageous synergy effect of different criteria. According to Equation (32), this new analytical model can be simplified as the conventional analytical model by adjusting the weight coefficients: On this basis, the weight coefficients can be determined by comparing the relative importance of different strength criteria, and the following procedure can be utilized to determine the weight coefficients using analytic hierarchy process (AHP) [53,54]:…”

Section: Geofluidsmentioning

confidence: 99%

“…In the above-mentioned studies, different criteria have been developed and employed to conduct WSA, most of the studies recommended to use the M-C, Mg-C, and ML criteria for WSA [8,[38][39][40][41][42][43][44][45][46][47][48][49][50][51][52]. However, the collapse pressure does not comply with different strength criteria, and some of the authors indicated that the best strength criteria are different for various well trajectories under different stress regimes [52,53]. In other words, the use of any single strength criterion is difficult to predict the collapse pressure accurately.…”

Section: Introductionmentioning

confidence: 99%

“…In other words, the use of any single strength criterion is difficult to predict the collapse pressure accurately. In view of this point, Zhang et al [53] proposed a new CPM of vertical wells by integrating the advantageous synergy among the M-C, D-P, ML, and Mg-C criteria, where each strength criterion is assigned a weight coefficient, and their results indicated that this new model can provide a much better comprehensive coverage for WSA, particularly the collapse pressure prediction. The greatest advantage of this new model is the advantageous synergy among several different criteria, but the current model is just suitable for vertical wells.…”

Section: Introductionmentioning

confidence: 99%

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Analytical Model of Wellbore Stability Analysis of Inclined Well Based on the Advantageous Synergy among the Five Strength Criteria

Shi

Zhang

et al. 2023

Geofluids

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The proper drilling mud density is vital for wellbore stability maintenance, which relies on both stress distribution on the borehole wall and rock strength. Thus, the selection of rock strength criterion is vital for wellbore stability analysis (WSA), and several strength criteria have been developed and employed to perform WSA, but the real collapse pressure does not comply with any single strength criterion. Therefore, to accurately predict the critical mud weight against wellbore collapse, an analytical model of WSA was proposed for inclined wells based on the advantageous synergy among the five types of strength criteria, such as the Mohr-Coulomb criterion, Mogi-Coulomb criterion, Drucker-Prager criterion, modified Wiebols-Cook criterion, and modified Lade criterion. The predicted results among these analytical and five conventional models were compared under three kinds of typical stress regimes, such as normal, strike-slip, and reverse faults. Finally, five kinds of typical oil and gas field data were collected to further verify the accuracy of this new model. The results indicated that different models predicted different collapse pressure, owing to the Mohr-Coulomb criterion ignoring the intermediate principal stress ( σ 2 ), so as to always give the greatest collapse pressure, followed by the present analytical model and the Mogi-Coulomb criterion, while the other three types of strength criteria gave different results, because of the difference in the influence of σ 2 , while the present analytical model integrated the advantageous synergy among the five strength criteria. The prediction error of the conventional analytical model ranges from 9.4 to 34.2% with an average of 22.1%, while the prediction error of this new model ranges from 2.3 to 12.5% with an average of 7.1%, so that the present analytical model has much higher accuracy than that of any single strength criterion. In addition, this new analytical model can be simplified as the conventional analytical model by adjusting the weight coefficients.

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Section: Geofluidsmentioning

confidence: 99%

Section: Geofluidsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Analytical Model of Wellbore Stability Analysis of Inclined Well Based on the Advantageous Synergy among the Five Strength Criteria

Shi

Zhang

et al. 2023

Geofluids

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show abstract

“…Circulation loss is a common but complex occurrence during the drilling process. Downhole leakage considerable increases drilling cost and downtime [1][2][3], which often leads to serious accidents because leakage management is a tedious process [4]. Furthermore, the reduction in the height of the liquid column in the wellbore is reduced, resulting in a decrease in effective static liquid column pressure at the well's bottom; this may easily lead to an imbalance in the formation of pore pressure, causing overflow and even blowout [5].…”

Section: Introductionmentioning

confidence: 99%

Prediction of drilling leakage locations based on optimized neural networks and the standard random forest method

Zhao

et al. 2021

Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles

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Circulation loss is one of the most serious and complex hindrances for normal and safe drilling operations. Detecting the layer at which the circulation loss has occurred is important for formulating technical measures related to leakage prevention and plugging and reducing the wastage because of circulation loss as much as possible. Unfortunately, because of the lack of a general method for predicting the potential location of circulation loss during drilling, most current procedures depend on the plugging test. Therefore, the aim of this study was to use an Artificial Intelligence (AI)-based method to screen and process the historical data of 240 wells and 1029 original well loss cases in a localized area of southwestern China and to perform data mining. Using comparative analysis involving the Genetic Algorithm-Back Propagation (GA-BP) neural network and random forest optimization algorithms, we proposed an efficient real-time model for predicting leakage layer locations. For this purpose, data processing and correlation analysis were first performed using existing data to improve the effects of data mining. The well history data was then divided into training and testing sets in a 3:1 ratio. The parameter values of the BP were then corrected as per the network training error, resulting in the final output of a prediction value with a globally optimal solution. The standard random forest model is a particularly capable model that can deal with high-dimensional data without feature selection. To evaluate and confirm the generated model, the model is applied to eight oil wells in a well site in southwestern China. Empirical results demonstrate that the proposed method can satisfy the requirements of actual application to drilling and plugging operations and is able to accurately predict the locations of leakage layers.

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Combined effect of anisotropy and uncertainty on the safe mud pressure window of horizontal wellbore drilled in anisotropic saturated rock

Tran

Phi

et al. 2022

International Journal of Rock Mechanics and Mining Sciences

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A New Analytical Model to Evaluate Uncertainty of Wellbore Collapse Pressure Based on Advantageous Synergies of Different Strength Criteria

Cited by 7 publications

References 40 publications

Analytical Model of Wellbore Stability Analysis of Inclined Well Based on the Advantageous Synergy among the Five Strength Criteria

Analytical Model of Wellbore Stability Analysis of Inclined Well Based on the Advantageous Synergy among the Five Strength Criteria

Prediction of drilling leakage locations based on optimized neural networks and the standard random forest method

Combined effect of anisotropy and uncertainty on the safe mud pressure window of horizontal wellbore drilled in anisotropic saturated rock

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