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

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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

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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. DEPTH

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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 [m3] 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

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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.

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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 [m3]

75.69

Abaqus [m3]

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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