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Rock Mechanics for Natural Resources and Infrastructure 
SBMR 2014 – ISRM Specialized Conference 09-13 September, Goiania, Brazil 
© CBMR/ABMS and ISRM, 2014 
 
SBMR 2014 
New Approach For Estimating Cavings Volume To Avoid 
Wellbore Instabilities 
 
Renato Gutiérrez Escobar 
Wellbore Stability Research Group, Bucaramanga, Colombia, renato.gutierrez@correo.uis.edu.co 
 
Zuly Himelda Calderon Carrillo 
Universidad Industrial de Santander, Bucaramanga, Colombia, calderon@uis.edu.co 
 
Yair Andres Quintero Peña 
ECOPETROL, Bucaramanga, Colombia, yair.quintero@ecopetrol.com.co 
 
SUMMARY: Most of the problems caused during drilling wells, such as pipe sticking, poor 
wellbore cleaning, sidetracks and even wellbore lost, are generated by some phenomena manifested 
in wellbore wall, such as Break-out, Wash-out y Kea-seat, which give origin to some slides of the 
wellbore wall known as cavings, the above problems and their effects contributes to increase the 
non productive time. 
 Currently, the caving volumes are used as a warning signal of wellbore instabilities during real 
time monitoring, since according to its morphological classification and produced volume represent 
kind of wellbore damage and its critical nature respectively. Considering the above aspects, the 
main aim of this research is to propose a new approach to estimate cavings volumes, in order to 
identify the kind of wellbore failure and the corrective actions in real time. Besides it can simulate 
the most critical aspect of the problem predicting the cavings volumes and the depth which they 
come from in order to prevent and mitigate them, thus reducing the non productive time during 
wellbore drilling. 
 In this new approach, a simulation of drilled wellbore is carried out using the Finite Elements 
Method taking into account the failure criterion and the material constitutive model to each cell of 
the simulation mesh, these considering the rock mechanical properties, mud weight and in situ 
stress state, in order to quantify the cells volume that failed in the simulation and reproduce the 
cavings volume of wellbore wall that would be produced during drilling. 
 An analytical approach is proposed in order to validate the results of the simulation. It consists 
approximating the cavings volume to the volume of a triangular prism, and calculating it by using 
geomechanics parameters such as in situ stresses, break-out angle and its width, mud weight and 
pore pressure. All these geomechanics parameters were obtained from wellbore logs. 
 
KEYWORDS: Cavings, Abaqus, Finite Element Methods, Breakouts, Wellbore Instabilities 
 
 
1. INTRODUCTION 
 
Simulation techniques have been needed by the 
petroleum industry in order to solve many field 
problems reducing uncertainties associated 
geomechanical and surfaces processes. This 
implies new technology developments to make 
investments more feasible since they could 
decrease economical risks to make drilling 
process more safe. 
 During drilling operations, the non productive 
time can make the petroleum wellbore 
economically unfeasible due problems such as 
pipe stucking which is caused by a high cavings 
volume in the borehole wall. The problem is 
identified only when cavings arrives to surface 
during field operation. The principal aim of this 
paper is to present a methodology that allows 
predicting cavings volume generated during an 
instability event by using geomechanics 
simulation with the Abaqus software. This way 
to predict wellbore instabilities makes it easier 
 
 
 
 
SBMR 2014 
to reduce the non productive time while drilling 
the wellbore. 
 Currently it does not exist a tool that allows to 
predict cavings volume before finishing drilling 
process, therefore the analytical approach and 
Abaqus simulation offer a great opportunity to 
improve drilling process decreasing the non 
productive time. 
 
 
2. MOHR COULOMB FAILURE 
CRITERIUM 
 
The Mohr Coulomb strength criterion describes 
the rock failure at different confining pressure 
while performing a few triaxial tests (Abaqus, 
2011). This criterion is represented by plotting 
the Mohr circle for the rock stress state in terms 
of maximum and minimum principal stresses 
(Fjaer, 2008). The failure envelope of Mohr 
Coulomb is the best straight line touching these 
Mohr circles, see Fig 1. 
 
 
Figure 1. Mohr-Coulomb Criterium 
 
 Next equation describes failure envelope for 
Mohr-Coulomb envelope 
 
 (1) 
 
 The Mohr Coulomb criterion asumes that 
failure does not depend on the intermediate 
principal stress effect and failure will occur 
when: 
 
 
 
 (2) 
 (3) 
 
 
 
 
 
 
 
 
 
 
3. PROPOSED METHODOLOGY 
 
In order to quantify the cavings volume, this 
paper proposes two different methodologies to 
determine it, analytically or by using Abaqus 
simulation. 
 
3.1. Analytical cavings volume 
 
It proposes to determine cavings volume from 
Kirsch equation (Zoback, 2007): 
 
 
 
 
 
 
 Solving for Breakout angle becomes: 
 
 
 
 
 
 
 From Breakout angle, it can determine 
Breakout width thus (Garcia, 2006): 
 
 
 In order to quantify cavings volume, one 
assumption is made: the cavings volume is best 
represented by a triangular prism volume, see 
Fig 2 and Fig 3. 
 
 
 
 
 
 
 
 
 
 
 
 
FAILURE ENVELOPE 
 
FAILURE ZONE 
SAFE ZONE 
 
 
 
 
SBMR 2014 
𝐿𝑂𝑁𝐺.𝑇𝑅𝐼𝐴𝑁𝐺. = 𝐶𝐴𝐿𝐼 − 𝐵𝑆 
𝑊𝑏𝑜 = 𝜋 − 2𝜃𝑏 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 2. Approaching of the cavings area to triangle 
area. Zoback, 2007. 
 
 
 
 
Figure 3. Approaching of the prism volume to cavings 
volume 
 
 Finally the analytical cavings volume is given 
by: 
 
 
 
 
 
 
3.2. Cavings volume using Abaqus simulation 
 
To determine this volume, the software Abaqus 
was used providing its inlet parameters of a 
geomechanical model. It assumes that width 
breakout is the only failure mechanism present 
in the wellbore. 
 The paragraph below it describes the 
simulation model used to quantify the cavings 
volume. 
 
3.2.1. Simulation Model 
 
A petroleum wellbore was simulated with 
diameter of 0,31 m in 3D (third dimension) of 
one rock lithology to a 2622 m in depth. Only 
11 m in depth was simulated to decrease 
computational cost (Schutjens, 2010), see Fig 4, 
thereafter it was multiplied by 10 to reach the 
whole rock lithology thickness of 110 m, 
assuming symmetry in properties behavior 
(Eckert, 2011). It highlights for the wellbore a 
finer mesh density in the near wellbore region 
comparing to the coarser mesh density in the 
outer section (far field region) (Chatterjee, 
2003) where the state of stress should be given 
by the homogeneous far field stresses (Mora, 
2005), see Fig 5. 
 
 
Figure 4: Sketch of the simulation model 
 
 
Figure 5: Zoom of the wellbore 
 
 
 
LENGTH TRI. = CALI – B.S. 
LENGTH TRI. DEPTHSBMR 2014 
3.2.2. Simulation Steps 
 
This simulation was divided in three steps 
(Mackay, 2011), in the first step it provided the 
model with the inlet parameters, boundary 
conditions and initial state of in-situ stress. The 
second step includes the use of the Abaqus 
geostatic function, which allows achieving the 
equilibrium between the state of stress, applied 
loads and boundary conditions. The third step is 
denominated Static step, which include a mud 
pressure in order to simulate the drilling process 
iterating to determine the state of stress during 
this process (Botelho, 2008). 
 
3.2.3. Failure in Abaqus 
 
In order to determine how many finite elements 
fractured during the drilling process, it was 
applied to simulation model an Abaqus failure 
indicator, which established finite element 
failure when it passes from elastic zone to 
plastic zone depending on the stress and strain 
conditions (Abaqus, 2011), see figure 6. 
 
 
Figure 6: Abaqus Failure Indicator 
 
 
4. EXAMPLE 
 
In order to apply the proposed methodology a 
real case was used with data from a Colombian 
field. This geomechanical model took into 
account parameters such as strength, rock 
mechanical properties (cohesion, angle of 
internal friction, young modulus, poisson ratio, 
permeability and porosity), it also included pore 
pressure, mud weight and in situ stress state. 
 With all these data and the use of the Mohr 
Coulomb failure criterion the state of rock in 
specific conditions was evaluated, in order to 
determine if studied rock fractures and how 
many cavings will form. Next assumption, was 
that the only failure mechanism present in 
wellbore was width breakout in order to 
calculate the cavings volume both analytically 
and by Abaqus simulation. 
 The data used in this paper is resumed in table 
1. 
 
Table 1: Wellbore properties 
SIMULATION MODEL DATA 
PROPERTIES MAGNITUD 
Model Volume [m
3
] 1100 
Wellbore Radio [m] 0.31 
Mud Weight [MPa] 48 
Young Modulus [MPa] 13793 
Poisson Ratio 0.2678 
Cohesion [MPa] 4.39 
AIF 31.6 
Porosity 0.26 
 [MPa]
 16.886 
 [MPa] 11.819 
 [MPa] 18.448 
 
 Effective stresses were used; where the 
maximum horizontal stress is acting in Y axis, 
the minimum horizontal stress is acting in X 
axis and the vertical stress is acting in Z axis 
both analytically and by Abaqus simulation. 
 
 
5. RESULTS ANALYSIS 
 
5.1. Results of the simulation static step 
 
In this step it simulates the drilling process 
whose results obtained in Abaqus were 
compared with those obtained analytically, 
hence Fig 7 shows that greater magnitudes of 
elastic strain are obtained in the minimum 
horizontal stress direction (X axis), which is 
correct according to width breakout 
characteristics. Negative signs in the elastic 
 
 
 
 
SBMR 2014 
strains magnitudes are caused by compressive 
stresses, whereas positive signs are caused by 
tension stresses. 
 
 
Figure 7: Elastic strain in X axis 
 
5.2. Calibration of the simulation model 
 
This calibration was based on Kirsch equations 
(Fjaer, 2008) to calculate the axial, tangential 
and radial stresses analytically (Zoback, 2007) 
and then they were compared to with those 
stresses obtained by using of Abaqus 
simulation. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 Figures 9, 10 y 11 show the comparison 
between analytical stresses and simulation 
stresses. A very good match is shown. 
 
 
Figure 9: Radial stress vs Wellbore radio 
 
 
Figure 10: Tangencial stress vs Wellbore radio 
 
 
Figure 11: Axial stress vs Wellbore radio 
 
5.3. Validation of Abaqus simulation 
 
This step it calculates the simulation cavings 
volume that subsequently is compared to the 
cavings volume estimated with the prism 
triangular approach. Fig 12 illustrates the 
PEMAG identifier (Plastic Strain Magnitude), 
that Abaqus offers to determine the failure of 
finite elements if its magnitude is different to 
zero (Abaqus 2011). As shown in the figure 
below, it is seen that width breakout 
characteristics at the borehole, where indicates 
that zones with different color to dark blue have 
fractured. This assertion matches to the 
wellbore behavior when it was drilled. 
 
 
 
 
SBMR 2014 
 
 
Figure 12: Plastic Strain Magnitude identifier 
 
 
6. COMPARISON OF RESULTS OBTAINED 
BOTH ANALYTICALLY AND BY ABAQUS 
SIMULATION 
 
Table 2 shows the cavings volume magnitude 
determined by using the prism triangular 
approach (Analytical) and the determined by 
Abaqus simulation, highlighting a good match 
between them. 
 
Table 2. Comparison of cavings volumes 
Volumen de cavings Magnitude 
Analytical [m
3
]
 75.69 
Abaqus [m
3
]
 54.93 
 
 
 
 
 
 
 Achieving this match, it could predict the 
cavings volume that would produce during 
wellbore drilling decreasing the non productive 
time caused by pipe stuck due an excessive 
cavings volume. 
 
 
CONCLUSIONS 
 
An analytical approach was developed to 
determnine cavings volume for width breakout 
failure mechanism as the only failure 
mechanism present in the whole wellbore. 
 
 The results showed a % error of 27 %, which 
means an acceptable match between cavings 
volumes determined both analytically and by 
Abaqus simulation. 
 
 With this methodology it can predict cavings 
volume generated during drilling process in a 
near wellbore to zone where data comes from, 
decreasing associated uncertainties and non 
productive time. 
 
LIST OF SYMBOLS 
 
 Shear Stress 
 Normal Stress 
 Cohesion 
 Angle of Internal Friction 
 
 Major Principal effective stress 
 
 Minor Principal effective stress 
 Uniaxial Compressive Strength 
 Failure Plane Angle 
 Mud Weight 
 Pore Pressure 
 Maximum Horizontal Stress 
 Minimum Horizontal Stress 
 𝜃 Breakout Angle 
𝑊 Breakout Width 
 Caliper Data 
 Bit size 
 Radial Stress 
 Tangencial Stress 
 Wellbore Radio 
 Vertical Stress 
 Axial Stress 
 Analysis Radio 
 Angel between 
 Poisson Ratio 
 
ACKNOWLEDGEMENTS 
 
I want to thank especially to wellbore stability 
research group for their support, patience and 
dedication. 
 
 
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Abaqus documentation 6.11, abaqus y u ’ 
manual, Dassault systemes Simulia. 201. 
Botelho, F. V.: Análisis numérico del comportamiento 
mecánico de sal en pozos de petróleo, Tesis de 
maestría PUC, 2008. 
 
 
 
 
SBMR 2014 
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