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Correlation Between Microseismicity and Reservoir Dynamics in aTectonically Active Area of ColombiaJ.G. Osorio, SPE, G. Peuela, SPE, and O. Otlora, BP Exploration (Colombia) Limited

Copyright 2008, Society of Petroleum Engineers

This paper was prepared for presentation at the 2008 SPE Annual Technical Conference and Exhibition held in Denver, Colorado, USA, 2124 September 2008.

This paper was selected for presentation by an SPE program committee following review of information contained in an abstract submitted by the author(s). Contents of the paper have not been reviewed by theSociety of Petroleum Engineers and are subject to correction by the author(s). The material does not necessarily reflect any position of the Society of Petroleum Engineers, its officers, or members. Electronicreproduction, distribution, or storage of any part of this paper without the written consent of the Society of Petroleum Engineers is prohibited. Permission to reproduce in print is restricted to an abstract of not morethan 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of SPE copyright.

Abstract

BP operates the Cusiana volatile oil field and the Cupiagua gas condensate field in the Andean Mountains foothills provinceof Colombia (Fig. 1.). In 1992, a permanent seismic network of ten surface stations was installed in Cusiana and Cupiagua to

obtain data for seismic hazard models necessary for the design of field infrastructure. The network is now in its sixteenth year

of continuous operation. Currently, an average of 1000 microseismic events per month is recorded. The resulting

seismological dataset is of high quality covering a range of seismic magnitudes down to about 1.0 on the Ritcher scale.

Over time, the Cusiana-Cupiagua Seismic Network (CCSN) has been used for different purposes. During the past few

years, it has become increasingly evident that the network and its data is an invaluable asset for evaluation of conditions

relevant to production/injection operations within the reservoirs and adjacent areas.

From the reservoir characterization and production operation standpoints, microseismic monitoring (also known as

passive seismic) has had two main applications in Cusiana and Cupiagua: (i) to identify production/injection induced high

transmissibility pathways and their temporal variations, and (ii) to image the orientation, extension, complexity, and temporal

growth of hydraulic fractures.

This paper is focused on the first of these applications: how microseismicity has been used as a surveillance tool to track

movement of reservoir fluids away from the wellbore. A short description of the seismic network is provided. Then, themethodology for data interpretation is discussed. Finally, partial results are presented showing how microseismicity

monitoring is being applied to: (i) assess transmissibility changes due to stress and pore pressure changes through time, (ii)

identify potential reactivation of pre-existing weak planes, and (iii) calibrate numerical models to improve history matches.

Analysis of the data shows a strong correlation between reservoir dynamics and production induced microseismicity in

Cusiana and Cupiagua Fields with great potential as a surveillance tool for improved reservoir characterization and

management.

IntroductionOil and gas production and injection change the pore pressure and the stress state in the reservoir. These changes give rise to

a change in volume of both reservoir fluids and reservoir rock. The volumetric behavior of the reservoir fluid is controlled by

the fluid composition and the change in the pore pressure and is not the subject of this paper. The volumetric response of the

reservoir rock depends on the mechanical properties of the rock material (matrix and pre-existing fractures) and the combined

effect of changes in pore pressure and stress state.

Conventional reservoir engineering incorporates the implicit assumption that the local stress state within the reservoir

remains constant with time. Thus, no deformation of matrix and natural fractures, caused by stress changes, take place during

the reservoir producing life. In this case, reservoir dynamics are governed only by changes in pore pressure. However, field

observations show that the magnitude and direction of production/injection induced stresses may change throughout the

reservoir with time (Saltz 1977; Avashthi et al. 1991; Teufel and Ferrel 1990 and 1992; Cornet and Jones 1994; Wright et al.

1995; Wright and Conant 1995).

These changes in the stress state, combined with changes in pore pressure, may have significant effects on dynamic

reservoir behavior. In particular, natural fracture deformation associated with production/injection induced stresses may

affect transmissibility and, therefore, productivity. From the geomechanics standpoint, fracture deformation is equivalent to

the reactivation of pre-existing discontinuous planes, which manifests itself as microseismic activity. Most of these

microseismic events have much less energy than the smallest earthquake that can be felt by a human at the earths surface.


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The correlation between microseismicity and reservoir dynamics depends on the degree of fracture deformation due to

pore pressure and stress changes induced by production/injection operations. This paper discusses the mechanisms

connecting microseismicity with injected fluid movement into the reservoir. Field evidence from Cusiana and Cupiagua

showing the correlation between microseismicity, local changes in in-situ stresses and preferential flow directions of injected

fluids are presented.

Observations indicate that the reactivation of fractures networks induce preferential flow in the direction of the maximum

horizontal stress. These preferential flow directions may change with time due to local stress variations which depend on

changes of production (pressure) conditions such as changes in flow rates, conversion from producers to injectors, infillwells, etc.

The paper includes a discussion on how microseismicity has been applied to calibrate reservoir simulation models using

the observation that microseismic events collected through time exhibit alignment, which is correlated with injection-

production imbalance. Then, improved model calibration is achieved by transmissibility increase in areas with observed

microseismic events.

Theory and definitionsThis section defines basic terms and explains the basic theory required to understand the combined effect of pore pressure

and stresses changes on bulk rock (matrix and fractures) response and its relationship with microseismic events and reservoir

dynamics. This section is intended to cover only very basic terms used in the context of this paper; it is oriented to readers

who have limited background of geomechanics fundamentals.

Formations are subjected to stresses derived from the overburden and the regional tectonic loading. These stresses can be

resolved into three perpendicular principal components: the vertical, minimum horizontal, and maximum horizontal stresses,

V , h , and H , respectively. In the Colombia foothills the Andes mountains tectonic forces dominate and, therefore, h

and H are the smallest and largest of the three components. In a regional scale, magnitudes of the principal stresses are of

the order of 0.75, 1 and 1.2 psi/ft for h , V and H , respectively. The direction of H is approximately North West

South East. However, there is evidence of local spatial variability in stress magnitudes and directions, which is to be expected

due to continuous changes in reservoir pressure due to production conditions.

The relationship between reservoir stresses and pore pressure is defined in terms of the effective stress, defined by the

effective stress law (Fjaer et al. 1992):

p = .(1)

In Eq. 1, and are effective and total stress, respectively; is a dimensionless variable called Biots parameter,

which is a measure of the contribution of pore pressure to the effective stress; p is pore pressure.The effective stress is a measure of the actual stress carried by the solid skeleton of the rock. Under the non-stressed state

(i.e., when both the pore pressure and the total stress equal atmospheric pressure), the effective stress is zero. Any change in

the pore pressure and/or the total stress will cause changes in the effective stress. Biots parameter , which depends on the

compressibility of the bulk rock and rock grains, defines how changes in the total stress and/or pore pressure interact to reach

a given effective stress state. In the reactivation processes of fracture networks, is usually approximated to unity; thus, Eq.

1 can be written as:

fp= . (2)

In Eq. 2, fp is the fracture pore pressure. Fig. 2a illustrates the effect of increasing fluid pressure on fracture sliding

(reactivation). The size of the Mohr circle indicates the differential effective stress ( )hH while its position depends on

fluid pressure and potential changes in local stresses due to pore pressure changes. In general, increasing fluid pressuresreduces effective normal stresses and shifts the Mohr circle toward the fracture reactivation envelope. However, depending

on the stress path (a measurement of local total stress changes due to pore pressure changes), the fracture reactivation

envelope could also be reached by pore pressure reduction. In the case of a strong rock, such as in the Cusiana and Cupiagua

Fields, fracture reactivation must occur prior to failure of the intact rock, which has a failure envelope further to the left

(Fig.1a). Sliding on fractures due to shear stresses acting parallel the fractures ( ) is suppressed by normal effective stresses

( fnn p= ) that press the opposing adjacent matrix blocks together (Fig. 2b). Sliding occurs when the ratio of these

stresses equals the coefficient of fracture static friction, , given by (Zoback 2007):

fn

r

p=

. (3)


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In Eq. 3, r is the shear stress that causes fracture sliding (reactivation), and n is the normal stress acting on the

fracture. The coefficient of static friction is equivalent to the slope of the fracture reactivation envelope in Fig. 1a and

typically falls in the range 16.0 . The shear and normal stresses acting on the fracture planes are functions of the

principal effective stresses, H and h , and the angle between the fracture planes and H . Thus some fractures are

more favorably oriented for reactivation than others.

In Fig. 3a(Zoback 2007), a series of randomly oriented fractures are shown. As pore pressure increases, the Mohr circle

moves toward the fracture reactivation envelop and a subset of pre-existing fractures begin to slip as soon as the fracturereactivation envelope is exceeded (those shown in red in Fig. 3b). Fracture planes that form angles between 25 and 35

degrees with H are usually the most optimally oriented fractures for reactivation. Movement along these pre-existing

fractures manifests itself as microseismic activity.

The energy associated to microseismicity events generated by fracture reactivation radiates as a compressional (P) wave

traveling at the P-wave speed followed by a shear (S) wave traveling at the slower S-wave speed (Crampin et al. 1991).

Strategically located geophones can record signals that can be analyzed to locate the source of the emissions. Location is

determined by distance and direction from the receiver. Distance to the event can be obtained by knowing the velocities of

the P and S waves and the lag times between their arrivals. Direction is known from polarization of particle motion of the P

wave, which is along the path connecting the event and the receiver. When several receivers are deployed simultaneously,

event locations may also be determined by triangulation by knowing the velocity of the P waves.

The analysis of split shear waves from microseismicity has shown to be a valuable technique to detect the main

orientation and intensity of open fractures in the reservoir. The method is based on the fact that shear-wave propagating

through rocks with aligned fluid-filled fractures will split into two waves, a fast one polarized parallel to the predominantopen fracture direction, and a slow one, polarized perpendicular to it ( Fig. 4). The time delayed between the fast and slow

wave is proportional to the fracture density, or number of fractures per unit volume (Rial 2005).

Cusiana-Cupiagua Surface Seismic NetworkThe CCSN was set up early in the development stage of the fields (1992) on a rugged topography and at the average

altitude in the network's area of approximately 1640 ft above sea level. The region average temperatures are about 26C and

relative humidity around 80%. These foothills, stretching all along the eastern Colombia, mark the limit between the stable

South America plate (Guyana shield) and the North Andean Block.

General Configuration

The basic shape of the network follows the shape of the fields, and thus the general geological strike. The dimensions are

approximately 50 miles (North-South) by 9 miles (East-West). The average distance between stations is 4 miles.

The configuration of the network, illustrated in Fig. 5, is certainly below the optimum, mainly in the extension of net

coverage towards East and West.

Hardware

The instrumentation of the CCSN consists of 18 surface seismological stations, each composed by a Digital Acquisition

System (DAS) and a three components sensor. The DAS units use 4 Gb compact flash memories for continuous microseismic

events recording storage, global positioning system time accuracy, Ethernet connectivity, among many other features that

allow a reliable network operation and maintenance

Processing Scheme

Data anal ysis

The scanning of all available data streams on screen for identification of event waveforms is usually a straightforward

activity. All local event waveforms are extracted and added to an event database, even if only recorded on a single station.

Phase readings

The phase reading is done visually, for both P and S waves and with all three components on screen. S-phases are read onchannels with clear onsets. Filtering is used as little as possible; very noisy seismograms are low-pass filtered, for events with

only few stations.

Magnitude calculation

Calculation of duration magnitudes is performed mainly to overcome the fact that occasionally S-waves are saturated;

thus the magnitudes are not calibrated for local conditions, but measured in a consistent way.

Hypocenter location

Routine locations are calculated with hypocenter location software. In some cases, single-station location routines for

polarization analysis of 3D-waveforms are used.

Advanced processing

Data from the CCSN, being recorded with three component sensors, allows determination of the basic shear-wave

splitting parameters, which are polarization angles and time delays between the two split S-waves. This information leads to


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models of the fracture directions in the rock mass, among other parameters, and can eventually also reflect changes in the

elastic properties of the media, due to injection or production of liquid or gas.

CCSN Objectives

At first, the CCSN was used to obtain data for seismic hazard models needed for the design of field infrastructure.

Because the region is seismically active, monitoring of local and regional seismicity in a risk reduction context has also been

a main objective. However, it has become increasingly evident that the network and its data is an invaluable asset for

evaluation of conditions relevant to understand reservoir performance.

Correlation between Microseismicity and Fluid Injection TrackingMicroseismicity monitoring can be used to map injected fluid movements in the reservoir. The mechanism connecting

microseiemicity with fluid movement within the reservoir can be summarized as follows: (i) fluid production/injection causes

changes in pore pressure; (ii) pore pressure changes cause variation in the in-situ stresses and deformation (sliding or

reactivation) of natural fracture networks; and (iii) reactivation on natural fracture networks induces microseismic events and

alters the permeability of the system. As mentioned earlier, the preferred direction for permeability enhancement by natural

fractures reactivation is between 25 and 35 degrees from the direction of H . Changes in production/injection conditions,

such as conversion of injectors to producers and new infill wells, may induce local changes in the magnitude and/or direction

of H and, therefore, temporal changes the preferential flow directions.

The case study of the effects of water injection into well Cusiana well TS26 demonstrates the strong correlation between

microseismicity and fluid injection in the reservoir (Garcia 2006). Over a period of 1032 days water was injected in the

reservoir at a wellhead average pressure of 4500 psi except for the interval starting on day 607 when, because of operationalproblems, injection wellhead pressure decreased to 1250 psi. It then increased gradually until reaching the average pressure

of 4500 psi on day 826. Microseismicity was monitored before starting water injection. Figs. 6a and 6bshow the injection

rate and the number of events per day, respectively, as function of time. The time scale in Figs. 6a and 6b include 120 days

before starting injection. A total of 2800 microseisic events were recorded during the test time. The epicenters of these local

events are shown in Fig. 7which also includes the direction of H in the Cusiana Field.

Several evetns are observed from Figs. 6 and 7: (i) before starting injection, the intensity of microseismic events is

negligible, (ii) the increase in the number of events per day is immediate as soon as injection starts, and (iii) the intensity of

microseismic events is proportional to the injection rate. These observations clearly support the strong correlation between

microseismicity and fluid injection. Furthermore, the cloud of microseismic events exhibits an elliptical shape with the major

axis aligned with the H direction. This is consistent with the orientation of fracture planes that are optimally oriented for

shear reactivation (see previous section). This later observation indicates that: (i) it is actually the reactivation of natural

fracture networks that induces the microseismic events (the temporal and spatial proximity between injection and mircro-

earthquake generation also provides evidence that the injection triggered the microseismicity) , (ii) the preferred orientation

for permeability enhancement and, therefore, the preferential flow direction for injected fluids, is NW-SE, and (iii)

microseismicity can be used as a tool to determine the local orientation of H and its probable variation with time (this is

essential input information for any geomechanics model).

The distribution of shear-wave polarizations from the injection test time is plotted in Fig. 8. The polarization of the faster

split shear waves displays approximately parallel (red dots) and perpendicular (green dots) to H ; however, the greatest

concentration of polarizations take place in the H direction indicating that during the injection period most of the fluid

moved in the NW-SE direction (the geometry of the swept area is elliptical with major axis aligned with H direction).

Current interpretation of the structure indicates that the flow component perpendicular to the H direction is generated by

fold-related fractures. A relevant fact from Fig. 8 is the gap of events observed in the injection period encompassed by days

607 and 826 corresponding to period of low wellhead injection pressure. This reveals once more the strong correlation

between microseismicity and reservoir dynamics.Fig. 9 displays the distribution of shear-wave polarizations through rose diagrams. Each rose diagram refers to a two-

month period. The red and green lines represent the relative amount of open fractures sub-parallel and sub-perpendicular to

the H direction, respectively. This is a measurement of the relative amount of fluid moving in each one of these directions.

An important feature observed from Fig. 9 is that shear-wave polarizations change with time. These changes indicate that

local effective stresses are varying with time and induce temporal changes of preferential flow directions. Changes of

production/injection conditions in a well and its offset wells will alter the local pressure field which, in turn, changes the local

stresses magnitudes and, very probably, stress directions. Any change in stresses magnitudes and/or directions open pre-

existing natural fractures in the direction of the new local maximum stress and tend to close fractures in other directions.

Needless to say, this dynamic behavior has implications to reservoir management. In addition, these observations lead

reservoir engineers to move towards a more realistic modeling condition in which components of the reservoir static model

become dynamic variables. For example, the transmissibilities connecting adjacent cells could vary with time and pressure.

These changes in transmissibilities depend on production conditions such as well locations, perforated intervals, production


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rates, etc. A complete discussion of the effect of production conditions on potential permeability changes is presented

elsewhere (Osorio, et al. 1997, Osorio et al. 1998).

Fig. 10presents a plot of the arrival time difference between the shear and compressional waves (S-P plot which to the

events distance). This plot provides information on preferential flow directions with depth. As observed from Fig. 10, for the

observation time selected from this study, injected water moved predominantly in the H direction (NW-SE) in the

intermediate and lower parts of the formation, while in the upper part of the formation, the preferential trajectory of flow was

in the direction of fold related fractures. Several facts could explain these differences in preferential flow trajectories between

units at different depths. Physical explanations include differences in fracture intensity and orientations, in pore pressure and,therefore, in effective stresses, in local principal stress orientation and in fracture properties. Practical impact of this behavior

is interesting and is currently under further study.

Numerical Model CalibrationAn additional strong correlation between microseimicity and reservoir dynamics is observed from the application of

microseismicity to numerical model calibration. A well calibrated reservoir model can be a tool to reliably predict future

reservoir performance if a set of reservoir description parameters can be incorporated to reproduce past production history as

outlined elsewhere (Calvin and Dalton 1990). Unfortunately, to arrive at a unique data set is almost impossible, and

alternatives to understand uncertainty impact of reservoir description on future performance using a reservoir model have

been proposed (Williams et al. 2004).

However, regardless of the approach reservoir engineers and geoscientists take to calibrate a reservoir model, subsurface

teams face the challenge of integrating data coming from different sources that most of the time is averaged information from

different scales (time, space). Most of the time, a good general picture about how the reservoir looks like can be drawn duringthis data integration process and model calibration, but sometimes data remains outside of the picture waiting for a consistent

story that explains its existence.

In particular, the Cusiana field numerical model has gone through several efforts for developing a calibrated reservoir

model, reliable for production prediction. As a result, a history matched model helped to define and to successfully

implement a gas injection redistribution strategy where produced gas injection in the crest is going to be progressively moved

to the flank of the structure (Soto et al. 2006).

During the model calibration process, conventional strategies for history match were used with limited effectiveness.

However, the model was not able to reproduce GOR increase at wells located on the flank of the structure, and at the same

time, reservoir pressure at the crest was higher than measured. This observation was explained by the lack of communication

between the crest and the flank in spite of the improvement in the geological description.

A solution was to increase the transmissibility perpendicular to the structure crest allowing better movement of injected

gas towards the flank. Since the selection of reservoir areas to increase transmissibility is not unique, microseismicity was

used to guide the best areas for increasing injected gas flow. Cusiana reservoir depth and complex structure setting make the

use of time-lapse seismic for model calibration impossible although elaborated approaches to use 4D seismic are available

(Stephen 2006).

Microseismicity events collected over time exhibit alignment that can be correlated with the injection-production

imbalance. For a particular year, Fig. 11 shows a very strong correlation between the total volume injected and the

concentration of events in the area close to injectors. In fact, the energy of those events, expressed as the cumulative moment,

is proportional to the cumulative volume injected as illustrated in Fig. 12.

Based on these observations, the subsurface team chose the areas for increasing transmissibility using the cloud geometry

of production-induced microseismic events, improving production history with the numerical model (Fig. 13). The residual

model mismatch in GOR was attributed to the lack of vertical resolution of the numerical model, which creates excessive

fluid mixing not observed in the field.

Microseismicity event understanding as well as data from other sources were combined, where possible (Fig. 14), to

represent a much consistent view of the subsurface, which improved reservoir understanding and the creation of strategies to

increase oil recovery.

ConclusionsMapping passive seismics in Cusiana and Cupiagua fields has revealed a strong correlation between reservoir dynamic

performance and production induced microseismicity. Fluid production/injection causes changes in reservoir pore pressure

and, therefore, in local effective stresses. The changes in effective stresses cause natural fracture deformations which, in turn,

change local transmissibilities and triggers microseismic events. The interplay of these two latter effects determines the

relationship between microseismicity and reservoir dynamics (pressures and fluid saturations among other factors). Several

highlights concerning this correlation and its great potential as a reservoir surveillance tool are noted here:

1. Cloud geometry of production-induced microseismic events is elliptical with major axis aligned with the maximumstress direction, indicating that, at a given time, existing preferential flow directions are sub-parallel to the current,

local maximum stress directions. As a consequence, microseismicity is a potential surveillance technique to track


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fluid movement associated with changes in the magnitude and/or direction of local principal stresses induced by

local fluid production/injection operations.

2. Shear-wave polarizations changes with time confirm that production-induced changes of local effective stresses(magnitudes and/or orientations) bring temporal changes in local preferential flow trajectories. This observation

suggests that preferential flow trajectories could be controlled by managing induced stresses, controlled by changes

in local production conditions. This performance may have important implications on reservoir management.

3. Arrival time difference between the shear and compressional waves (S-P plot) indicate that microseismicity also

represents a potential surveillance tool to track selective fluid movement with depth.4. With respect to reservoir simulation, active tectonic areas present challenges to reservoir modelers from different

points of view. Static models are no longer static. Pore pressure changes influence more than material balance.

Rocks deform. Passive seismic appears revealing a relation between production/injection strategies and reservoir

performance. Based on those observations, we can conclude as outlined in this paper: (i) microseismic events can be

correlated with production/injection schemes that alter the natural state of rocks, (ii) understanding of

microseismicity leads to a more robust description of a reservoir although implementation of that description

requires much more modeling to be effectively used for prediction, and (iii) rocks react consistently to

production/injection induced perturbation. Pre-existing weak planes also observed at rock samples are reactivated

causing a measured wave response at surface. Therefore, data collected from different sources and scales should be

reconciled.

Finally, it should be emphasized that although field observations in Cusiana and Cupiagua, as describe in this paper,

clearly indicate that microseismicity is a potential surveillance tool to improve reservoir characterization and management.

Additional and more specialized applications will allow to obtain further benefits of this technology.

Nomenclature

p = pore pressure, m/Lt2, psi

fp = fracture pore pressure, m/Lt2, psi

= Biots parameter

= coefficient of fracture static friction

= total stress, m/Lt2, psi

h = minimum horizontal stress, m/Lt2, psi

H = maximum horizontal stress, m/Lt2, psi

n = normal stress, m/Lt2, psi

v = vertical horizontal stress, m/Lt2, psi

= effective stress, m/Lt2, psih = minimum horizontal effective stress, m/Lt

2, psi

H = maximum horizontal effective stress, m/Lt2, psi

n = normal effective stress, m/Lt2, psi

= total stress, m/Lt2, psi

r = fracture reactivation shear stress, m/Lt2, psi

AcknowledgmentsThe authors would like to thank SDLA Partners (BP Colombia, Tepma and Ecopetrol) for allowing publication of this paper.

Also we would like to show our gratitude to Corporacin OSSO for their continuous effort on micro seismic data acquisition,

processing and interpretation.

ReferencesAvasthi, J.M., Nolen-Hoeksema, R.C. and El Rabaa, A.W.M. 1991. In-Situ Stress Evaluation in the McElroy Field, West

Texas. SPEFE (Sept 1991): 301-309. SPE-20105.

Calvin, C. M. and Dalton, R.L. 1990.Reservoir Simulation. Monograph series, SPE, Richarson, Texas 13.

Crampin, S. and Lowell, J.H. 1991. A Decade of Shear-Wave Splitting in the Earths Crust: What Does it Mean? What Use

Can We Make of it? Ans Should We Do Next?. Geophys. J. Int. 107: 387-407.

Cornet, F.H. and Jones, R. 1994. Field Evidences on the Orientation of Forced Water Flow with Respect to the Regional

Principal Stress Directions. Proc.First North American Rock Mechanics Symposium/The University of Texas at Austin,

Austin, Texas, 61-69.


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Fjaer, E., Holt, R.M., Horsrud, P. and Raaen, A.M.. 1992. The Effective Stress Concept. In Petroleum Related Rock

Mechanics. Elsevier Science, Chap. 1, 37-39. New York City, NY.

Garcia, A. 2006. Caracterizacin de una Cuenca Petrolera con Sismicidad Pasiva a partir de Anisotropa Ssmica y Anlisis

de Repetidores. PhD dissertation, Universidad del Valle, Cali, Colombia.

Osorio J. G., Chen H-Y, and Teufel L.W. 1997. Numerical Simulation of Coupled Fluid-Flow/Geomechanical Behavior of

Tight Gas Reservoirs. Paper SPE 39055 presented at the SPE Fifth Latin American and Caribbean Petroleum EngineeringConfrenece and Exhibition held in Rio de Janeiro, Brazil, 30 August 3 September.

Osorio J. G., Chen H-Y, and Teufel L.W. 1998. A Two-Domain, 3D, Fully Coupled Fluid-Flow/Geomechanical Simulation

Model for Reservoirs with Stress-Sensitive Mechanical and Fluid-Flow Properties. Paper SPE 47397 presented at the

SPE/SRM Eurock Conference held in Trondheim, Norway, 8-10 July.

Rial, J.A., Elkibbi, M. and Yang, M. 2005. Shear-Wave Splitting as a Tool for the Characterization of Geothermal Fractured

Reservoir: Lessons Learned. Geothermics34: 365-385.

Salz, L.B. 1997.Relationship Between Fracture Propagation Pressure and Pore Pressure. Paper SPE 6870 presented at the

SPE Annual Technical Conference and Exhibition, Denver, Colorado, October 9-12.

Soto, L., Penuela, G., Benavides, I., Martinez, M., Castiblanco, I., and Chaves, I. 2006. Gas-Injection Redistribution

Revitalizes a Mature Volatile Oil Field: Cusiana Field Case Study. Paper SPE 103593 presented at the SPE Annual Technical

Conference and Exhibition in San Antonio, Texas, 2427 September.

Stephen, K. D.; Soldo, J., MacBeth, C., and Christie, M. 2006. Multiple-Model Seismic and Production History Matching:

A Case Study. SPEJ11(4): 418-430. SPE 94173 PA.

Teufel, L.W. and Farrel, H.E. 1990. Distribution of In Situ Stress and Natural Fractures in the Ekofisk Field, North Sea.

Proc.Third North Sea Chalk Symposium, Copenhagen, June 11-12.

Teufel, L.W. and Farrel, H.E. 1992. Interrelationship Between In Situ Stress, Natural Fractures, and Reservoir Permeability

Anisotropy: A Case Study of the Ekofisk Field, North Sea. Proc. Fractured and Joined Rock Conference, Lake Tahoe, June

3-5.

Williams J. J, G; Mansfield, M.; MacDonald, D. G.; Bush, M. D. 2004. Top-Down Reservoir Modelling. Paper SPE 89974presented at the SPE Annual Technical Conference and Exhibition, Houston, Texas, 26-29 September.

Wright, C.A. et. al. 1995. Hydraulic Fracture Orientation and Production/injection Induced Reservoir Stress Changes in

Diatomite Waterfloods. Paper SPE 29625 presented at the SPE Western Regional Meeting, Bakersfield, March. 8-10.

Wright, C.A. and Conant, R.A. 1995. Hydraulic Fracture Reorientation in Primary and Secondary Recovery from Low-

Permeabilty Reservoirs. Paper SPE 30484 presented at the 1995 SPE Annual Technical Conference and Exhibition, Dallas,

Texas, October 22-25.

Zoback, M.D. 2007. Critically Stressed Faults and Fluid Flow. In Reservoir Geomechanics, Cambridge University Press,

Chap. 11, 340-377, New York City, NY.

SI Metric Conversion Factors

psi 6.894 757 E +00 = kPa

ft 3.048* E - 01 = m

mile 1.609 344* E - 00 = km

lbf-ft 1.355 818 E - 03 = kJ

*Conversion factor is exact.


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Fig. 1. Location map of the BP Colombia fields in Colombia.

(a) (b)

Fig. 2. Mohr circle showing stress evolution with production/injection time and fracture and reactivation envelop. The stress staterequired for fracture re-activation depends on the fractures orientation with respect to maximum stress orientation and the stresspath.


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(a) (b)

Fig. 3. Fractures occur with wide range of orientations. Not all fractures are permeable in todays local stress field. Those fractureswith a ratio of shear to normal effective stress between 0.6 and 1.0 are likely to slip during production/injection operations (modifiedfrom Zoback 2007).

Fig. 4. Schematic view of shear wave splitting. A shear wave splits into two: one fast parallel and one slow perpendicular to theopen fractures in the medium (after Rial 2007)


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Fig. 5. Map of the Cusiana and Cupiagua Network showing its current stations distribution (squares) and geometry). Major faultsare represented by bold dark lines and lease areas by white lines.

(a) (b)

Fig. 6. Injection rate (part a) and the number of events per day (part b) as function of time. Before starting injection, the intensity ofmicroseismic events is negligible. Also, the intensity of microseismicity is proportional to the injection rate (modified from Garcia,2006).


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Fig. 7. Epicenters of the local events recorded during the observation time selected to monitor microseismicity triggered by

injection in Well Cus TS26. The right side illustrates the average direction of H in Cusiana (part b, after Last et.al.).

Fig. 8. Distribution of shear-wave polarizations of the events presented in Figure 7. The greatest concentration of polarizations take

place in the H direction indicating that during the injection period most of the fluid moved in the NW-SE direction. The geometry

of the swept area is elliptical with major axis alight with H direction. (Modified from Garcia, 2006).

4 km4 km4 km


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Fig. 9. Rose diagrams representing the distribution of shear-wave polarizations. The red and green lines represent the relative

amount of open fractures sub-parallel and sub-perpendicular to the H direction, respectively. This is a measurement of the

relative amount of fluid moving in each one of these directions (modified from Garcia, 2006).

Fig. 10. Arrival time difference between the shear and compressional wave (S-P plot). For the observation time selected in this

study, injected water moved predominantly in the H direction (NW-SE) in the intermediate and lower parts of the formation, while

in the upper part of the formation, the preferential trajectory of flow was in the direction of fold related fractures (modified fromGarcia, 2006)..


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Fig. 11. Bubble map of Cusiana fluid production and injection. There are mainly three water injectors, which are responsible formost of the microseismicity events in that year. In the map, there is a strong alignment of event related to Cusiana TS26 waterinjector.

y = 0,1607x + 0,0876

R2= 0,9897

0,0

0,4

0,8

1,2

1,6

2,0

0 2 4 6 8 10 12 14

Cumulative water injection, million bbl

Cumulativemoment,lbf-ftx

1015

Fig. 12- Energy associated to microseismic events is proportional to the cumulative injection in the Cusiana TS26 area (modifiedfrom: Jones, M. 2002. Consultancy Presentation, University of Portsmouth, Portsmouth, UK).

CSTS265 km

Production/Injection Microseismic events

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Production/Injection Microseismic events


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Fig. 13. To allow gas in the crest of the structure to move towards the flank, permeability multipliers were used increasingtransmissibility from 2 to 20 times.

Fig. 14. X-direction transmissibility multipliers are located in areas of the reservoir using data from different sources such as core,UBI and structural curvature analysis. In areas where data from different sources area available such as the area of RC2W well,microseismicity confirms the extension in the reservoir of heterogeneity observed at the well level.

spe 115715 ms p (paper principal)

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