Articulos Yac de Gas

8/10/2019 Articulos Yac de Gas

1/27

Integrated Study for Water Management in a Highly Heterogeneous

Water-Flooded Reservoir Western Desert Egypt

Ahmed Aly and W John Lee,

S.A. Holditch Associates, Znc.

rnanagement in a highly heterogeneous, multilayered,

ihase reservoir becomes complicated when poor

--i:rrization of the reservoir by conventional methods

.T:S

fine-scale resolution of the model.

o b l e mecomes evident when the oil production rate

-C

Xayat-Yasser,LowerBaharyiaresefvoir in the western

c

f

Egypt dropped 30 , and water cut increasedfrom

'7 .

Conventional14-layermodelingcouldnot explain

-qd changes in reservoir behavior.

: z ~ t i o nof well-log analysis, geology, and two-

--onal seismic through geostatistic modeling techniques

A?

a 30-layered reservoir model that was used to calibrate

2

,-dimensional, three-phase numerical stimulation

X

greater resolution in the model, we were able to

L

r.

match the reservoir performance on three levels; field

L individual well level, and zona1 level (production

r z g data).

y u l t of this study, we were able to identify promising

far redevelopment, plan strategies for optimizing

>ir management, and visualize approaches for

m= uture management and development of similar

-Y~'ods in the area.

:3per presents details of this study and our

L n n d a t i o n s for future field development.

Khalda Petroleum Co. (Khalda) discovered the Hayat field

in 1986, when the Hayat-1X was dnlled. The Yasser field

was discovered in 1987 when Yasser-1 was drilled. The Hayat

Yasser field is located in the southeastern portion of the

Khalda West Concession, south of the Salam field, in the

Western Desert of Egypt. Oil production in this field peaked

in August 1995, at an average of 10,000 STBID, f r ~ mhe

Lower Bahariya formation, and then started to declie rapidly.

The reservoir fluid in the Lower Bahariya reservoir is a

volatile oil that may grade into black oil in the deeper poftion

of the reservoir. Khalda has requested that the reservoir

simulation model use a black oil configuration. This is an

adequate representation of the reservoir fluid if the pressure

throughout the simulation model remains above the

bubblepoint. As the reservoir pressure in the field drops below

the bubblepoint, large amounts of gas will come out of

solution and will ovemde the oil production. This may result

in a loss of oil production and production of a large amount

of gas. In addition, our reservoir simulation model will not

be adequate to handle this situation. As a result, one of our

main objectives in developing this field is to maintain the

reservoir pressure above the bubblepoint. In addition, we

need to develop the optimal scenario to recover the maximum

amount of oil.

In the rest of the paper we will present the results of the Hayat

Yasser, Lower Bahariya study &d present our conclusions

and recommendations based on these results.

In this section, we describe the reservoir model used to

simulate the history of the Lower Bahariya reservoir in the

Hayat Yasser field.


2/27

Memorias

/

Proceedings

On a basis of our experience with grid design and optirnization

and after considering various smaller grid-block sizes, we

built the final fine-grid model using comer-point geometry

grids to honor the faults in the field. We also applied local

grid refinement (LGR) around the severa1 wells. Fig 1

presents the grid we used over the geostatistical model. We

applied LGR to help with our history match. .Based on the

geostatistical study, we preserved the vertical layering profile

of 30 simulation layers. The resulting model dimensions were

39 x 23 x 30. This resulted in a reservoir simulation model

with 26,910 main grid cells coupled with 32 locally refined

grid cells.

The PVT data, the relative permeability and the capillary

pressure data for the reservoir simulation mbdel were

developed and discussedby McCain.

In this section we present the results of our history match of

the Lower Bahariya reservoir. The reservoir performance

history match helped us in determining the original oil in

place for the Hayat Yasser field with great accuracy.

For the field history match, we attempted to honor the

observed oil and watej production rates and water injection

rates. In general, we matched the production performance

as a function of time at the field level to a tighter tolerance

than at the well level. A tighter tolerance at the field level is

reasonable because field data generally have less error than

individual well data. Well data usually have more uncertainty

because of production testing measurement errors and

inaccuracies associated with allocating field data to individual

wells and further to individual reservoirs.

Initial history matching adjustments focused on overall

reservoir performance including oil, gas, and water

production and pressure. Subsequent adjustments were made

to improve individual well matches.

Table

presents our history matching adjustment pararneters

and the history matching criteria.

Fig 2

shows the field oil, water, and gas production rates.

We can see from Fig 2 that the reservoir simulation model

honored the observed field oil and water rates. There is much

uncertainty in the recorded gas rate data, and the model

matched the field performance adequately, given the

uncertainty in these data.

Fig 3

shows the gasloil ratio (GOR). The match is good and

confirms our bubblepoint match.

Fig 4

shows the water-cut plot match, which is also gooc

We can see that we matched the arrival time of the watt-

well.

Fig

5

shows the history match of the cumulative oil, water

and gas production for the Hayat Yasser field.

Fig 6

shows the history match of the field water injectic-

rate and cumulative water injection. The match is good.

Fig

7

shows the pressure history match for the Hayat Yassc-

field. Al1 the observed and simulated pressure data ar

adjusted to the datum level (-5475 subsea true vertical depti-.

Fig

6 shows the pressure match for the A-sand (whic-

incorporates most of the hydrocarbon-bearing formation. Tr::

pressure matches for the C sand (which is mostly below tk

oil/water contact and represents the bottom part of the C

sar..

geological layers) are also presented in

Fig 7. Fig

7 shoii

a good pressure history match and adds confidence to

ti :

volumetric estimate of the OOIP from this reser\-c

simulation model.

WellPerforinance istory Match

In this sectionwe discuss the individualwellhistory match?.

This added a second level of history matching on individu-

wells to the field-wide history match. This ensured g k .

history matches in different parts of the field @eally). 1

addition, this will assist with accurate forecasting, resen

development, and management of the Hayat Yasser, Lou:

Bahariya reservoir.

Figs 8

to

1

show some representative individual well histc:

matches for this field.

The good individual well history matches provided the ba-

for forecasting using the reservoir model.

uroduction Logging istc

The production logging (PLT) historymatch provides a

th-.

level of history match. Matching the PLT flow rate u.:

depth ensures a history match at the zonal level afterachiel

an acceptablehistory match at the total field level and at rr

individual well level areally. This third-leve1 history ma.

adds more verification and validity to the geostatistic

integrated model for the Lower Bahariya reservoir.

Accuracy of rates from production logs depends on

flui:

produced:

m For single-phase flow (especially water injection), intc

preted results are quantitative and potentially accurats

m

For two-phase, waterloil flow, results are less accurart

m For flow with a gas phase, results are only qualitativf


3/27

ms

inproduction log interpretation are as follows:

= m - p h a s e njection wells,

f

0

w phax

liquid flow (oillwater),f 0

-mxphase flow (oil/water/gas),

f

0

~ g p i m e

low in deviated wells, very large errors

I.s

U

3

present some representativeproduction logging

LT

m h e s . These figures show that the model did a

-

_ xi

job of matching the zona1 production.

For the Lower Bahariya reservoir, we determined the movable

hydrocarbon for the A-sand (simulation layers 1 to lo), where

most of the hydrocarbon lies. In addition, we summed the

MHPV distribution of each layer into a summed MHPV for

the entire reservoir. Fig

14

presents the distribution of the

sumrned MHPV for the Lower Bahariya A-sand (layers 1 to

10) initially (1989) before any production from the Hayat

Yasser field.

Fig 15

presents the summed MHPV at the end

of the history match (-1997). As shown in

Fig

15

severa1

areas in the Hayat Yasser field have much more highly

movable oil (marked in red and yellow) than the rest of the

reservo.: We focused on those areas for our redevelopment

and infill drilling locations in the forecast runs.

sr y matching the historical reservoir performance,

u

t ~

ovable hydrocarbon technique2 to optirnize

~mu @ormance of this reservoir. The biggest challenge

r phase of the project was the complexity and

L N

of the reservoirsystem. Wellswere selectively

sony a few layers at a time, rather than in al1

3 x cmce.

Thus, the developmentof each reservoir layer

We needed a simple and systematic approach

1s

e anking the areas of the reservoir that were most

mmmsq or future development and infill drilling.

w

history match of this reservoir resulted in a layer-

.. m= distributionof current water saturation. However,

jlrmation alone is not sufficient to identify the most

mamaqareas

for redevelopment. Abetter indicatorwould

a m s related to potentially recoverable oil volume,

Aes into account porosity, net pay, and fluid

mmmm We selected the movable hydrocarbon technique

n

calculated it foreach grid block in the simulation

apier mg the following equation.

Forecasts

In this section we present the different forecast cases. We

designed our cases to forecastuntil the year 2008 and to shut

in and abandon the field when the field's total oil production

drops below 1,000 STBD.

We illustrate our optimal recovery case, which results in a

recovery factorof43 at theyear 2006. The optimalrecovery

case shows an additional recovery factor of more than 10

over the base (as-is) case. The optimal recovery case will

require drilling 11 new producers and 3 new injectors and

recompleting 6 shut-in wells as injectors.

Fig 16 shows field oil production forecast comparisons for

the base case, the recompletions case, and the optimal

recovery case. This showsthat we can increaseoil production

by around 160 . The field oil rate will go from around4,000

STBD to around 6,700 STBD if we develop the Lower

Bahariya using the optimal recovery scenario.

7758xhx@x S0 S,,)

ST acre =

Fig 17

is the field cumulative oil production forecast

O

(')

comparison for the three cases.

Fig 18

is a comparison of the forecasted gas production for

kas the follOwingadvantages for hel~ing ngineers

the three forecast scenarios. This indicates that even for the

6 ~ o f

reservoirforredevelo~mentandinfilldriuing

optimal recovery case, the gas production does not increase

above the levels we had in 1995, which means the pressure

m s a volumetriccalculation,which providesa direct

in this aggressive case did not drop below the bubblepoint.

bare of the amount of potentially recoverable oil in

The pressure-forecastplot illustrates this.

m

m of the reservoir.

Fig 19

is a comparison of the forecasted A-sand pressures

forthe forecast cases. This figure shows that the piesure in

d d r e p r e s e n t s movable oil, MHPV takes into account

the optimal

recovery

c se does not drhp below the

11that can be affectedby changes in wat~rflood

bubblepoint as we have aggressively manzged the reservoir

d n s .

and replaced the withdrawl volums with injected water.

m s equal to or less than zero for any areas of the

=oir that has oil saturationbelow Sdr, such as near

r an oil/water contact. The calculation of MHPV

The base case represents the as-is scenario. The base case

=

sclude a filter to automaticallyeliminate values of showeda recovery factor of around 33 at the end of the run

~ ~ i i ~ -ear or below zero.

(2004). We assumed that we would produce this field under


4/27

Memorias

/

Proceedings

the current operating conditions. In this case we have 9

producing wells and 10 injection wells.

The summed movable hydrocarbon pore volume map for the

A-sand at the end of the base case (2004) is presented in

Fig

20. We still see some red spots in the field, which means that

if we apply the base-case development scenario, we will leave

some unrecoverable reserves in the Lower Bahariya reservoirs

at the year 2004 when we abandon the field. Thus, we

conclude that this development scenario may not be the

optimal scenario for the development of the Lower Bahariya

reservoir in the Hayat Yasser field.

In this case we recompleted some of the watered-out

producers as injectors. The recompletion-forecast case

showed a recovery factor of around 32 at the end of the run

(2003). In this case we used the same number of injectors

and producers as the base case, and we recompleted some

watered-out wells as injectors.

We optirnized the recompletion case by doing severa1 runs

where we injected into the C sand in the wells that are down

structure. This resulted in helping the pressure in the field

without losing production due to early breakthrough and

watering-outof producing wells.

Fig

21

is the sumrned movable hydrocarbon pore volume

map for the

A

sand. We can see that at the end of this

recompletioncase in the year 2003 we have some bypassed

oil and reservesin the ground. Thisencouragedus to develop

the optimalrecoverycase and to go after the remainingoil in

the Lower Bahariya reservoir.

The optimal recovery case was designed as follows:

Recomplete

6

shut-in wells to injectors.

Drill 3 new injection wells.

Drill 11 new production wells.

Recomplete one new producer in the Hayat area

an injector to help maintain the field pressi.

after the well waters out.

Fig

22 shows the summed movable hydrocarbon pc

volume map for the optimal recovery case in the year

2 1

In this optimal run we effectively produce the hi-

accumulation pockets of movable oil.

The optimal recovery case resulted in a recovery factor of

around 43 at the end of the run (2006).

The optimal recovery case was developed after performing

multiple runs to investigate the optimal scenario to develop

the Lower Bahariya reservoirs. It included the input from

the Hayat Yasser team and the Production Enhancement Team

(PET) and the experience of the Holditch team3 in developing

heterogeneous, waterfiooded reservoirs.

We tried most of the possible locations for new wells

suggested by our movable hydrocarbon maps and the

independent work of the Production Enhancement Team. We

had two main objectives when developing this case.

Maintaining pressure above the bubblepoint.

Producing the maximum feasible cumulative oil from the

Lower Bahariya in the Hayat Yasser field.

This case proved to be the optimal case as it exceeded

economic lirnits set by the operatingcompany by a factoi

2.

As a result, we believe that the optimal recovery case will

the best scenario to develop the Lower Bahariya reservoi:

produce the maximum cumulative oil and to maint.

pressure above the bubblepoint. Also, we must take i:

consideration that the Lower Bahariya reservoir is higi-

heterogeneous and that it requires a phased developni.

approach and updating of the model periodically as new

L

become available (e.g., 3D seismic, new well logs, and y

data). We also recommend an aggressive managen?:

program of this field using the reservoir simulation

o

developed in this study.

Horizontal Well ase

In this case we investigated the feasibility of drill

horizontal wells to produce some undrained pocket.

movable oil in the Lower Bahariya reservoir. We found

two well-placed vertical wells will outperform a horizor

well in draining the Lower Bahariya reservoir. Thi.

reasonable because of the heterogeneous nature of the

L o

Bahariy a reservoir.

The development scenario of this case is the same a

y

las nuevas oportunidades que de ello se derivan.

'iicimientos de este campo son arenas compactas de

~ z i l i d a denor a 1mD y es prctica comnfracturarlas

r i c a m e n t e para obtener una produccin comercial de

Y ntegracin de la interpretacin de la ssmica

3D

del

in? n la caracterizacin de los yacimientos , el estudio

permiti proporcionar localizaciones de nuevos pozos

zrc

la marcha del estudio. Estos pozos, una vez

c . d o s , mostraron presiones de poro muy cercanas a la

- :a inicial de los yacimientos,

450

Kg/cm2. La estrategia

110 inicial, basada en la integracin de informacin

=a de ingeniera del campo, asegur el xito de la

etapa del desarrollo del Arcabuz-Culebra. A partir

r el

estudio integral jug un papel muy importante en

rt-arrollo de este campo. La produccin, que

---damente en un

70

proviene de la arena Wilcox

4,

:

k z e n t en mas de 600 ; se ha establecido un plan de

i

a l l o que involucra la perforacin de mas de

300

pozos

Zzw

y

extensin en un trmino de tres aos. En general

S 'r-ac7amiento de los nuevos pozos es de alrededor a

400

TC x las nuevas prcticas de fracturamiento ofrecen

-

de hasta

500

pies de extensin, lo cual favorece la

T~YL-vidadon relacin al espaciamiento.

g g

tapa del estudio integral se ha concentrado en

n modelo numrico de simulacin para las arenas

Wilcox, que ha permitido entender mejor la dinmica de los

compartimentos que definen los yacimientos compactos del

campo. En este sentido, la simulacin ha proporcionado

elementos que confirman que la ssmica

3D

en este campo,

no ha logrado definir algunas barreras o fallas que influyen

en el comportamiento dinmico del flujo. Es decir, se ha

observado que existen fallas o barreras subssmicas asociadas

a compartimentos. Estas observaciones han permitido

posicionar mejor los pozos de relleno en el desarrollo del

campo.

El modelo numrico construido en esta etapa ha sido validado,

ya que reproduce la historia de presin-produccin que el

campo ha experimentado durante su vida productiva. La

representacin espacial de las fracturas hidrulicas asociadas

a los pozos del campo represent un reto en la simulacin,

ya que no fue fcil garantizar soluciones numricas adecuadas

con un refinamiento local de malla arbitrario, adems del

alto costo de la simulacin bajo este concepto. Una vez

calibrado el modelo, se analizaron los siguientes escenarios

d produccin : es-amiento e m e pozos, lGgitud de

f r a c x y uso de compresin. Se realizaron corridas de

ensibilidad, con diferentes espaciamientos entre pozos, a

. .

fin de o~t imizar sta variable. Asimismo, se investia el

efecto de diferentes longitudes de fractura en la producci6p.

Finalmente se analizaron diferentes niveles de contrapresin

en los pozos y su rela cison la produccion. La t i g b 1

muestra la Cecuencia metodolgica aplicada en la etapa de

simulacin. Todos estnc pcrpnnrir\rre analizaron

econmicamente a fin de observar su impacto en los costos

de vroduccin.

La Figura 2 muestra un resumen de estos resultados.

Una tercera etapa del estudio integral, an en desarrollo, es

la simulacin dinmica de sistema integral yacimientos-

tubera-redes superficiales. El anlisis de escenarios de

produccin utilizando esta modalidad integral ofrecer una

mejor calidad en los estudios integrales de yacimientos de

Arcabuz-Culebra.

Los beneficios de un estudio integral utilizando tecnologa

moderna y una organizacin interdisciplinaria muestran en

los resultados del desarrollo del Campo Arcabuz-Culebra un

excelente ejemplo. Un incremento sustancial en la

productividad del campo se ha visto apoyada por una

organizacin basada en prcticas modernas de administracin

de yacimientos.

Las administracin moderna de yacimientos ha propiciado

cambios importantes en la organizacin y esquemas de

trabajo de las empresas petroleras, coadyuvando a maxi-

mizar el valor econmico de sus yacimientos.


13/27

Memorias / Proceedings

Los estudios integrales de yacimientos requieren de la

sinergia entre ingenieros petroleros, gelogos geofsicos

y petrofsicos, lo que se ha dado de manera natural en la

administracin moderna de yacimientos.

Los estudios integrales son la base de la planeacin del

desarrollo exitoso de un campo.

El campo Arcabuz-Culebra, de la Cuenca de Burgos es

un ejem plo claro de los beneficios de la administracin

moderna de yacimientos y del empleo de nuevas tecno-

logas.

En

los ltimos cuatro aos la produccin d e gas de este

campo se ha visto sextuplicada.

Satter, A. y Thakur, G .: Integrated Petroleum Reservoir

Management: A Team Approach , Tulsa, OK , PennWell

Books, 1994.

Halbouty, M.T.: Synergy is Essential to Maximum Re

covery, JPT, July 1977,750-754.

Craig, Jr.,

F.F.

Willcox, P.J., Ballard, J.R. y Nation,

W.R.: Optimized Recovery Through Continuing Inter-

disciplinary Cooperation, JPT, Julio 1977, 755-760.

Harris, D.G. y Hewitt, C.H.: Synergism in Reservoir

Management- The Geologic Perspective,

JPT, Julio

1977,761-770.

Thakur, G.C.: Reservoir Man agement: A Synergistic

Approach, Artculo SPE No. 20138 presentado en SPE

Permian Basin Oil and Gas Recovery Conferei-

Midland, TX, Marzo 8-9, 1990.

Wiggins, M.L. y Startzman, R.A.: An Approach

to

servoir Management, Artculo SPE No. 20747 pr f-

tado en Reservoir Management Panel Discussion.

65

Conferencia y Exposicin Tcnica de SPE.

.

Orleans, LA, Septiembre 23-26, 1990.

Satter, A, , Varnon, J.E. y Hoang, M.T.: Reservoir

'

nagement: Technical Perspective, Artculo SPE

22350 presentado en el SPE Internacional Meetir.,

Petroleum Engineering, Beijing, China, Marzo

21..

'

1992.

Jourd an, C. A. y Erling, E.T.: Integrating

3D

Seisn: .

Multidisciplinary Reservoir Modeling Projects,

.

Enero 1997,30-32.

Tiab,

D

y Kumar, A. : Applications of the p'D F U E .

to Interference Analysis, JPT

,

Aug. 1980, 1465- - -

Bourdet, D., Whittle, T.M., Douglas, A.A. y Pirar:

M.: A New Set of Type Curves Simplifies Well

Analysis, World Oil, May 1983, 95-104.

Vazquez, R., Mendoza, A, , Lopez, A, , Linares.

Bernal, H.: 3D Seismic role in the Integral Studb

Arcabuz-Culebra Field, Mexico, The Leading Edgs.

1997, Vol. 16, NO. 12, 1763-1766.

Berumen , S., Sanchez, J.M. y Rodriguez, F.: A Str-

for Additional Developm ents in the Burgos Basin -

Arcabuz-Culebra Gas Field , Artculo SPE No.

presentado en International Petroleum Conferencc

Exhibition of M exico, Villahermosa, Tab. Mxico.

\ ' .

3-5, 1997

reas de Drene Elemento de Malla de

Simulacin

Pozo

Fractura

tiempo

entre pozos mts)

igura

1

Metodologta de

o Simulaci np r un

modelo de

se tores

de

yacimiento

04


14/27

3Wm mn wm V W so m

squemas

de spaclamientw

igura

2

Incrementos econmicos respecto del caso base para diferentes esquemas de

espaciamientos

FERNAN DO RODRIGUEZ D E

LA

GARZA

:sde 1996 es Gerente de Administracin de Yacimientos en la Subdireccin de Tecnologay Desarrollo Profesional

de Pemex Exploracin

y

Produccin.

e incorpora PEP en 1991y fue comisionadoa la UNAM, donde fue profesor y jefe de la Seccin de Ingeniera

trolera en la Divisin de Estudios de Posgrado de la Facultad; actualmentees profesor de asignatura.

ue 1989 a 1991 fue contratado por PETROBRAS y comisionado al Departamento de Ingeniera Petrolera de la

Universidad de Carnpinas en Sao Paulo, Brasil, donde fue profesor e investigador

1982a 1989fue investigadordel InstitutoMexicano del Petrleo,en la Divisin de Ingeniera de Yacimientos.

t u 1 ~ 8 2btuvo el grado de doctor en ingeniera petrolera en la Universidad de Stanford. En 1978 obtuvo el grado

le

maestro en ingeniera petrolera en la DEPFI-UNAM. Se gradu como ingeniero petrolero en el Instituto Politcnico

Nacional en 1973. De 1973 a 1978 trabaj para el

IMP

en la Divisin de Ingeniera de Yacimientos, en el rea de

simulacin numrica.

Su

rea de especialidad es la ingeniera de yacimientos, con nfasis en simulacin numrica de yacimientos

naturalmente fracturados.

a

publicado mas de

5

artculostcnicosenrevistasy memoriasdecongresos,tantointernacionalescomo nacionales.

a sido editor tcnico de SPE, y miembro de diversos comits tcnicos de SPE y de AIPM.

hi distinguido en 1987 con la Medalla Juan Hefferan , otorgada por la AIPM

y

en 1993 con el premio a la

Investigacin en Ingeniera Petrolera, otorgadopor el Instituto Mexicano del Petrleo.


15/27

Memorias Proceedinas

Integrated Reservoir Study Optimizes Development for a Communicating Gas

Volatile-Oil and Black-Oil Reservoir Complex

Nathan C . Hill Duane A. McVay Pavel A. Zliassov S. .-i

Holditch Associates n .

Brock E. Morris and D. Leigh D ick so~ :

Society of Petroleum Engirzet

An integrated reservoir study was performed to determine

the optimum development plan for two of three adjacent,

communicating reservoirs located in the Americas. The three

reservoirs are within one mile of each other, have three dis-

tinct reservoir fluids, and are in pressure equilibrium. The

lowest reservoir is gas, the next highest reservoir is a volatile

oil, and the highest reservoir is black oil. A compositional

reservoir model that includes al1 three reservoirs was built

using geophysical, petrophysical, and geological and engi-

neering analyses and was calibrated using production and

pressure data. Production data and reservoir modeling indi-

cate that there is movement of hydrocarbons between the

structures. With the calibrated model, we determined that

altemating water and gas injection WAG) in selected wells

offered the optimum future performance for the two oil res-

ervoirs.

The three reservoirs in this study are structural traps sepa-

rated by northw est-trending structural saddles. Th e reser-

voirs are named Reservoir A, B and C, as seen in the sche-

matic cross-section in Fig. 1 Reservoir A is the gas reser-

voir, while Reservoir

B

is the volatile oil and Reservoir

C

is

the black oil. Mosr of the w ells are on the crests of the struc-

tures. At the time of this study, there were 4 wells in Reser-

voir, 11wells in Reservoir B and 10 wells in Reservoir

C

Only

2D

seismic data w ere available over the reservoirs.

The reservoirs are located in an area without a gas market

and regulations do not allow flaring of the gas. Thu s, aIiy

produced gas from Reservoirs

B

and

C

has to be reinjected.

Thre e of the four active wells in the gas reservoir are used a s

observation wells. This study was performed to develop an

understanding of this complex reservoir system and

optimize futu re performance of the oil reservoirs.

Geological and Petrophysical Analyses

Zndicate Depositional Environment

Th e reservoir sandstones are shallow marine, strandpla

barrier, an d fluvial-deltaic deposits. The se sediments u c-

deposited along a retrogradational coastline. Faults bou

some of the basement h ighs and offset the reservoir s ar-

stone. Thu s, the thinness or absence of the sandstone str,

over the structurally high are as is a result of erosional t r L

cation. The se faults also affected depositional patterns

well as fluid migration. Fig.

2

shows the top of structb

ma p of the reservoirs.

We divided the reservoir sandstones into three p ri n ci ~

layers or flow units. Th e two productive intervals are r

UW and the LW layers. The G layer is the lowest layer a-

has no reservoir potential. Mineralogy and di ag en e~

control reservoir character of individual layers, which in t u

reflect the depositional setting of the layers. General

reservoir quality improves upw ard in the reservoir sandsto

as a result of coarser-grained sediments with higher quar

content being deposited in higher energy setting-

Th e G layer was m ost likely deposited below wave base

ir

low-energy marine environment.

Th e LW layer was deposited in a higher energy environm s-

than the G layer. The LW layer is afin e- to med ium -grain~

quartzarenite that is well cemented by quartz overgrou

t

that reduce intergranular porosity and the.size of m any por.

throats. Mu dston e clasts composed of clay minerals wsr.

deformed during compaction and further reduced effecti..

porosity and pore throat size.


16/27

r r

LW layer was deposited in a high-energy coastal envi-

l:.zlznt. It is a coa rse- to very coa rse-grain ed quar tzare nite

2 Aso is cemented by quartz overgrowths. Only minor

a re p r e sen t i n the UW laye r . Muds tone c l a s t s

~ ~ l r s i t e dn the UW layer were most comm only composed

-~~-bona t eock fragments. During diagenesis, many of the

- - x a t e clasts dissolved, creating secondary porosity that

. __

.-bed

_.

the reservo ir qu ality of this ayer.

cxtrophysical analysis included normalizing the log data

r 5

wells (some of which were from the same formation

r e r nearby fields), performing borehole corrections, and

- .mt ing the log data with the core data. The-calibrated

z s r e then used to determine values of porosity, water

;--=ion and shale content. The average effective porosity

e

LW layer is 13.2 , while the average in the LW layer

L

5 .

The petrophysical analysis of the core data did not

- i z e any flow barriers between the UW and LW layers.

-;

at ' the wells are clustered on top of the structures. To

the maps of net pay and porosity, the sandbody

retry

and reservoir layer trends were extended on the

of seismic amplitude analysis and published des-

- r o n s of the regional depositional setting and paleoslope

~--=on.

production from the field was from Well B10. Well

produced for more than 600 days before the second

r

-rarted production. Initial production from Reservoir

C

=ii

at about 1000 days. At about this time severa1 wells

Y :ompleted and began producing. Fig. shows the oil

a - t i o n rates from Reservoirs B and

C

with time

z n c e d to the start of production f rom Reservoir B .

:

hows that the pressures in al1 the reservoirs began to

c - igif icantly with the increase in production rates.

ZZT

oir

A

was not produced and Wells A7, A14, and A19

ujed as pressure observation wells. Fig. 4 shows that

S Iressures in A7 and A14 dropped as a result of the

- u - t i o n from Reservoirs B and

C,

although at different

- \t about 1400 days, gas injection was started in well

5

eservoir

B.

Fig. 5 shows the gas and water injection

111

Reservoir. B . Within 100 days of the start of gas

cm he measured pressures in Reservoir B start leveling

Fig

4). The production rates in Reservoir B were also

~ u do keep the pressure above the bubble point.

It initially tested o il at original solution GO R and remained

shut-in as a pressure observation well. Severa1 months after

the initial oil test, test data showed very high W OR and low

GO R. A few weeks later, the well was very high GOR while

maintaining high WO R. The test was about 7 0 days after the

start of gas injection and the initial theory was early break-

through. However, early gas breakthrough did not explain

the water production. Well B10 , which was in between the

injector and the test well, produced water free oil at original

gas-oil ratio. Th e conclusion was that gas expan ding in

Reservoir A pushed water from the saddle area up the

northeast flank of the structure toward are a of B 18. T he water

was followed shortly thereafter by gas migrating out of

Reservoir A. Th e reservoir study was

started.soon after this.

About 1700 days after initial production five wells were

drilled and RFT test measurements were taken. The RFT

data show that there is good lateral cornmunication within

the U W layer. The data also show that the LW layer pressure

was 9.5 to 38.7 kglcm2 (135 to 550 psi) higher than the UW

layer, and that this pressure difference is maintained even as

the pressure drops in both layers. The fact that the LW

pressure was declining from the original pressure shows that

there is vertical communication between the layers with

fluids migrating from the LW to the UW since there was

very little production from the LW itself. The pressure

difference between the two layers shows that the vertical

communication is limited. Considering the areal extent of

the reservoirs, the vertical transmissibility must be very small

to maintain this pressure difference. This lirnited vertical

communication between layers has a direct impact on

secondary recovery in the LW layer.

1

r ss su r uildi a t Data Supports

Estimates

and

Layer

Pressure buildup tests were analyzed on eight wells in

Reservoir

C

and seven wells in Reservoir B . The pressure

buildup tests that were m n early show that the UW layer has

a permeability of about 800 to 1000 md on the top of the

structures while the LW layer has permeability of 15 to 30

md: Pressure buildup tests in the U W layer that were run

after a significant pressure drop in reservoir pressure al1 show

indications of layer cross flow between the UW and LW

layers. As an example, the type curve plot in Fig. 6 shows a

bdziction Data Show Communication

buildup pressure test from Well C11. Reservoir simulation

.

history matching with a single well model was required to

z r rst

direct evidence of fluid migration within the

W

analyze the test. The analysis showed that crossflow was

as production test data on well B 18. Well B 18 is on

occurring and that only a minimum permeability could be

;

..rtheast corner of the top of the Reservoir B structure. obtained. These results confirmed the RFT results


17/27

Memorias Proceedinas

. .

Reservoirs

Fluid samples were analyzed from four wells in the three

reservoirs. The results, summarized in Table 1, show that

Reservoir A has a gas with a dew point, Reservoir

B

has a

volatile oil with a bubble point and that Reservoir C has a

black oil with a bubblepoint. Since it appeared there was

migration of fluid between reservoirs, one set of equation-

of-state EOS)parameters was developedto describeal1three

reservoirs. Since the objective of the study was the optimi-

zationof Reservoirs

B

andC, the three sampleanalysesfrom

these two reservoirs were used for calibration of the EOS

model.

A compositional reservoir model was built and then calibrated

using the pressure and production data. The objectives in

calibrating the model were to match the pressure responses

in the oil reservoirs Reservoirs

B

and C), match the gas and

water production in well

B18

and fit the general pressure

trend of the gas wells in Reservoir A. The approach was to

specify the oil rates and calculate the gas and water rates and

the pressures. The results of the pressure match from the

reservoir model calibration are shown in Fig. 7.

Al1 three reservoirs were initially at equilibrium at a

pressure of 327 kg/cm2

4656

psi) at a subsea datum of

2930.7m -9615 ft), which is below the water contact in al1

three reservoirs. As Reservoir B is produced and the

pressure is reduced, water migrates and the pressure drops in

Reservoir A, allowing the gas to expand. The gas expands

below the spill point and starts migrating into Reservoir B.

The gas-oil ratio match of Well

B

18 in Fig.

8

shows the early

gas-oil ratio increase caused by gas migration. The lines on

the graph are the model results, while the symbols are the

observed data. Although not shown, water migration

between the reservoirs causes a water-oil ratio in Well

B

18.

The pressure data and reservoir modeling also showed that

t h e ~re partial transmissibility barriers that limit communi-

cation within Reservoir A, the gas reservoir. This limited

comm unication between wells in the gas reservoir has a

significant impact on long term production performance in

Reservoir B.

At the time gas injection was started in Reservoir

B

it was

not determined if Reservoir C

was in cornrnunication. As

the pressure in Reservoir

B

leveled off, the data show that

the pressure decline changed in Reservoir

C,

indicating

communication.

ptimal R e .

~ s

. .

Alternatina Gas Znjection

To optimize performance of this reservoir complex, we con-

bined the reservoir model, an economic model and a wellborr

model. The economics were calculated an wellbore modc

The economics were calculed on an incremental basis ar .

were used to judge the various operational scenarios. Soni:

major factors affecting the economics were the costs of ns

wells and the operating costs for the gas and water injectii

facilities. The produced gas is reinjected because there is

r

market for the gas and it cannot be flared due to regulatior.

During the optirnization phase, cases were developed

investigate the sensitivity of different model paramete:

These included parameters affecting surface facilitis

comrnunication between the reservoirs, reservoir layer a:

fluid properties, and individual well production.

The results of our optimization showed that gas inject~~

should remained capped at the current capacity and tk-

water and gas should be injected in Reservoir C. T-

pressure in the UW layer in Reservoir B should

maintained above the original bubble point pressure

maintain gas miscibility until the oil production can:

economically support gas injection. This happens abou-

years after the end of the current history match. T-

pressure should then be allowed to drop but still maintair-

above the Reservoir C bubble point pressure. This d r o ~

ReservoirB pressure allows additional migration of gas fr

Reservoir A and increases cross flow from the LW to

r

UW layer, thus reducing injection requirements.

We determined that water-altemating-gas WAG) inject:

should be used to maintain reservoir pressure and optim

sweep in the UW layer. The alternating over-ride of :

miscible gas and underride of the water provides excel1:-

sweep efficiency. The permeability of the LW layer is

:

low to use WAG. We also determined that WAG injectior

the UW layer does not have a negative effect on recovep

the LW because of the pressure differential toward the

L-.

Secondary recovery in the LW found to be was

1 :

accomplished by injection of gas. The gas is miscible a

the oil, thereby reducing viscosity and improving cross fi

to the UW layer.

We also recommended adding severa1 wells to improvex

sweep, and we determined that horizontal wells in the L

layer provide an economically viable option if the drilli-

risks can be overcome.


18/27

The optimum recovery method in the

UW

formation

of Reservoirs B and is WAG injection.

The optimum recovery method is the LW in Reser

i~oirs and

C

is gas injection only.

Horizontal wells in

the

LW formation appear to be

sconomic; however, t he nsks associated with

hrizon-tal drilling in this area should

be

quantified

k t .

Reservoirs A, B and C are al1 in communication

through a common aquifer.

Gas is migratingfrom ~eservoir to the oil reservoir

in Reservoir

B

because of the decline in pressur in

Reservoir

B

There is limited vertical communication between

the

UW

and LW layers in Resenoir B and

C

Reservoir C

Bubblepoint 158 kg cm2

OM

2766 m

SS

Table 1- Summary of Reservoir Fluid Properties

Reservoir B

Bubblepoint224 kg cm2

OMI

2864

ReservoirA

Dewpoint308 kg cm2

MI 2931 m ss

Reservoir

A

B

C

- < S - s e c t i o n of Reservoirs A B nd C.

Saturation

Pressure

T Y P ~

Dewpoint

Bubblepoint

Bubblepoint

Saturation

Pressure

kg/cms2

308 4390)

224 3186)

158 2244)

Mole of

C7+

2.58

27.62

39.93


19/27

Memorius

/

Proceedings

rg. - l op oj imucnrrejor

ReservoirsA

B

nd C

lo

lo

P

-i

E

d flerewair c

-

o

1

O

1o

O 500 1 15 2 2 ?

Time, days

Fig. 3 Oilproduction rates from Reservoirs

B and C.

Fig. 4

Reservoirpressure history in

all

threr

reservoirs

34

~ ~ ~ l l

320

O

J ~ ~ ~

9

\

B

*

v v v

300

- 280

P

260

2

n

24

2

220

200

18

*N

- ResewoirB

O

All Wells

*+

X

-

-

@i

-

-

-

All Wdls

\&

ResewoirC d

B

-

-

-

l i ' i i i i i i i l i i i i l i i i i ~ i i i t

-500

O 500 lo 1500 2000

2500

%


20/27

d ater injection rates

B

1 E m E

Fig

6 Log plot of plo o presura buildup test

otofivm

We CII

1OOOOO

.

m

2 ~ a n n ~

Fig

7

- abmcion

of motiel

t

reservoupressures

-

-

-

-

-

Water Injection

I I J I I l l l l I I l I I l

r

lo

12 14 16 1800 2000 2200

.

-

-

-

-

-

1

'


21/27

Memorias Proceedings

Fig.

8

Calibrntion of model to gas oil ratio hislory

Manager of Reservoir Engineering Venezuela Division

S.A Holditch Associates, Inc.

B.S., Petroleum Engineering, Texas A M University

M.S., Petroleum Engineering, Texas A M University

Mr. Hill received a B.S. degree in 1983 and an M.S. degree

in

1984 in Petroleum Engineering from Texas AS

University. He joined S.A. Holditch Associates, Inc. part time in May 1984 and full time in January 1985.

principal area of responsibilityis the design and enhancementof computer models to assist in engineering evaluat

of projects. Recent software projects include well test analysis and production analysis programs. Mr. Hill

participated in engineering projects for litigation and presentation to state regulatory agencies. He has also

bc

involved in reservoir simulation, pressure transient analysis, well logging analysis, and well performance projectit

In 1998 Mr. Hill moved to the Venezuela Division to manage the reservoir-engineeringgroup.

i


22/27

Memorias / Proceedings

The Use of a Multi-Disciplinary Team Approach for the Reservoir

Characterization of a Mature Field, Alto de Ceuta, Block

VII

Lake Maracaibo, Venezuela

Gomez Ernest; Elphick R.

Y;;

Forrest G .

F;

Gustason E. R

McChesney D. E. Vivas M. A.; Doe M .

GeoQuest Reservoir Technologies Denver i

Gonzalez

J.

A. Rampazzo

M.

Chan B. Mora

J. L.

and Rivas O

PDVSA Caracas Venezuela ar

Ripple R. .4

ARCONICO Jakarta Zndone

The Alto de Ceuta (ADC) Field is located in the southeastern

part of Lake Maracaibo. The field was discovered in 1957

and has produced over 480 M MB O through 1997 from the

Miocen e Lagunillas and Eocene Misoa formations. The

field s structure is characterized by inversion of Eocene

through M iocene sediments along a convergent, left-lateral,

right-stepping zone of re-activated, rift-related, Jurassic

faults. Progressive deformation comb ined with changes in

the dynamics of the eastern Maracaibo microplate have

resulted in relaxation and tensional tectonics ac ross the AD C

high in the post-Miocen e. Th e later tectonic history affected

deposition of the Miocene and

served to compartm entalized

both the M iocene and E ocen e reservoirs.

A multidisciplinary team cons isting of engin eers, geologists,

geophys ic is ts and pe t rophys ic is ts was assembled to

characterize and simulate the field. Th e available data

included 3-D seismic, open hole logs from over

200

wells, 9

cores with routine core analysis, and production and pressure

measurem ents. Because of the complex stratigraphic and

structural nature of the AD C Field, it was especially imp ortant

to integrate data from al1 the disciplines to accurate ly

characterize the field. Pressure measbremen ts and production

history were combined with the seismic interpretation, log

analysis , core description, log correla tions , Statis t ical

Curvature Analysis Technique (SCAT) and mapping to define

During the past several years the

importante

of

u.

i n t e g ra te d mu l t i -d i s c ip l in a ry t e a m s in r e s e r \

charac te r iza t ion and s imula t ion has been recogniz .

In tegra t ion of the va r ious d isc ip l ines a l lo ws fo r

construction of geologic and reservoir models that

n-

accurately represent what is happening in the field. Alth o-

an integrated, multi-disciplinary approach is useful in fic

of any siz e, it is especially vital in m ature reser voirs that

-

comp lex structurally and stratigraphy. The subject of

paper, Alto de Ceuta Field (ADC), falls into this cates

and is located in the southeast com er of Lak e Maraca

Venezuela Figure 1).

A joint team of PDVSA and GeoQuest professionals

formed in late 1996 to study the Alto d e Ceuta Field.

first objective of the study was to construct a geologi,

static model of Alto de Ceuta using the available geologi..

geophysical, petrophysical and engineering data. Once :

reservoir characterization has been completed the g e o l ~

model will be validated through reservoir simulation

p

selected basis. The resulting dynamic reservoir model

then be used to optimize production. A t present tbe geoli.

model of the Alto de Ceuta Field is nearing completion

this paper will focus the methodologies used durins

construction and to a lesser extent on the results.

fault compartments . Engineering data also proved very

f i r s t s t e p i n an o v e r a l l in t e g ra te d r e s e r \

helpful in the stratigraphic correlations. characterization and simulation study is the constructior

the geologic model. The geologic model is static. That

:

reflects the state of the field based on the data available F .

it is built. No as sumption is made of what will happen

\

time and additional operating activities within the field.


23/27

:.urate geologic model incorporates data from geology,

T- ics, petrophysics and reservoir engineering (Figure

-- 1

onsists of the structure, isopach and property maps

:sjervoir.

. 9 geologic model is built it can be validated using a

-7ic model through numerical simultaion (Figure

3 .

The

-

.i.;tructure. isopach and property maps are input into

.

.:mulator. If the geologic model is indeed-an accurate

--z~ntationf the field, the production and pressure history

zs duplicated or matched he reservoir simulator. In

. this z i f ver happens on the initial attempt. A

Aely scenario is that the model will be reviewed and

e by the integrated technical team that built it (Figures

The Alto de Ceuta structure was a positive feature throughout

Miocene time. The Lower Lagunillas, Laguna and

Bachaquero members of the Lagunillas Formation are thinned

or absent over the feature, the result of non-deposition and/

or erosion. West of the Pueblo Viejo Fault, the Bachaquero

thickens abruptly. While faulting is much less pronounced

in the Miocene than the Eocene, changes in sand unit

thicknesses and facies due to minor fault relief exert a major .

influence on reservoir heterogeneity and quality. The

complex nature of the structure and stratigraphy at Alto de

Ceuta meant that the construction of an accurate geologic

model would require close intergration of the various

technical disciplines.

. :

J Several iterations may be necessary until an

.::~blc history match can be achieved. The resulting

--sd reservoir model is dynamic. That is the model

- sx with time and in response to different operating

The data available at Alto de Ceuta included various vintages

-70s. This dynamic feature allows the model to be used

and types. Cores of the Miocene and Eocene reservoirs were

E

prediction of field behavior using different operating

among the first pieces of data to be reviewed. otal of 9

---os From these various realizations the field operator cores were described for this study. Five of the c o r z e r e of

ct the optimal scenario that is the best solution given

wells within the field and the remaining 4 came from wells

. .

nomic and operating constraints.

immediately adjacent to the Alto de Ceuta Field. The cores

provided valuableinformationon depositionalenvironments

and reservoirproperties includingporosity and permeability.

In addition,special core analysis had been preformed on two

ro de Ceuta Field was discovered in 1957 and has

--


24/27

this task was to see what data was available, identify missing

logs, looking for inconsistencies and correcting the dig::

data sets and to build the data base that would be used for the

data to the original paper prints. After the digital logs as

remainderof the study. Thedata and specifictasksperformed corrected, environmental corrections were applied and r

duringthis stagewill be reviewed by disciplinein this section logs were normalized. This normalized data set was rk.:

(Figure 3).

used for the stratigraphiccorrelations and log analysis.

Y

sand, net pay,.average porosity and average water saturar:

were among the petrophysical properties calculated r

mapped for the Alto de Ceuta Field (Figure 3).

The geologists were responsible for developing the

stratigraphic framework that will be used through out the

field (Figure 3 . The first step of this process is to examine

the available core within the Alto de Ceuta Field and adjacent

areas. The cores provided information on depositional

environments, rock type and porosity and permeability.

PDVSA was able to provide valuable information on the

field and regional stratigraphy in the form of unpublished

interna1 reports. The core descriptions and previous PDVSA

geologic studies were then incorporated into the final

stratigraphic framework used for the study. The geologist

then took this framework, and aided by seismic, petrophysical

information and the pressure and production data, extended

the correlations to the remainder of the field (Figure 3).

Although the geophysicist had the primary responsibility in

developing the structure model for the field, the geologist

alsoplayed an importantrole The geophysicist and geologist

incorporatedthe regional structureas interpretedby PDVSA

and other workers into the Alto de Ceuta structural

interpretation, modifying it as dictated by the well and

seismic data. Statistical Curvature Analysis Technique

(SCAT) was used with the dipmeters to aid in the structural

interpretation. The Alto de Ceuta Field has had a complex

structural history resulting in multiple fault blocks with

different pressure and hydrodynamic regimes. Fine tuning

of the final smctural frameworkrequired inputof thepressure

and petrophysical (i. e.

oillwater contacts) data.

The seismic data quality at Alto de Ceuta rendered it suitable

only for gross structural interpretation. For this reason only

six horizons were interpreted; Laguna, Eocene Unconformity

(EUNC), Miosa B1, Misoa B6 Misoa C1 and Cretaceous

Colon. These seisrnic horizons were tied to the stratigraphic

framework developed by the geologist from the well control.

Structure maps of the seismic horizons and severa1 other

geologic markers were constructed and used to build the

structural framework of the field (Figure 3).

The petrophysicist s first responsibilty was to build a digital

log data base for the Alto de Ceuta Field that would be used

for log analysis and stratigraphic and seismic correlations

(Figure 3). This started with editing of the existing digital

The project engineers had two tasks during constructior

the geologic model. The first was to build the data base :

would be used in the geologic model. The second objecr:

was to prepare the data for an eventual reservoir simular.

study.

The largest component of of the engineering data base :;

.

the well histories (perforations, sleeve histories

L

completion data). Almost al1 of this data was in hard

c i

T

form and had to first be placed into a digital format. T

pressure and production data was allocated based on

i

stratigraphic correlations developed by the geologist

i

geophysicist. This pressure and production data playei

important role in fine tuning of the stratigraphicand strucrL--

frameworks (Figure 3). Along with static press- -

measurements, pressure transient tests (mostly press-

buildups), were evaluated to assist in identifying flow ba r :

(i. e. sealing faults).

The engineering data gathered and evaluated during built.

of the geologic model will be instrumental n the construcr~

of the reservoir simulation models. Data such as rela:

permeability, fluid properties, rock properties and

L:

histories will be used in the final reservoir simulationm@::

The geologic model as reflected in the individual reser.

models will serve as a basis for further understanding

history match proceeds.

Data integration occurred continuously during the reser.

characterization and building of the geologic model. Ha\ .

the project team work in close proximity to each other res~:- .

in discussion and enhanced the integration process. 1

structure, isopach and property maps that make up the

i

geologic model incorporated al1 the data sets availr-

(Figure 3). In this way it is anticipated that an accur.

geologic model of the Alto de Ceuta Field will be construi::

As stated previously a finalized geologic model is nor

available. However, based on some prelirninary results

;

conclusions can be drawn.


25/27

r

new geologic model for Alto de Ceuta Field repre-

ents

the complex stmcture and stratigraphy better than

~sv iousttempts.

litial volumetrics of the main Eocene B6 reservoir

zpea r

to match closely with figures from previous

=DVSA tudies. This allows for increased confidence in

::eologic model constructed during the study.

--:zgration of the various technical disciplines helped to

iplain and correct apparent discrepancies in the data.

of Economic Paleontologist and Mineralogist Special

Publication no. 37 p.375-386.

Ghosh S. Pestman P. Melendez L. and Zambrano E.

1996 El Eoceneo en la Cuenca de Maracaibo; facies

sedimentarias y paleogeografia: Vo Congreso Venezolano de

Geofisica 8 p.

Roure

F.

Colletta B. De Toni B. Loureiro

D.

Passalacqua

H.

and Gou Yves 1997 Within-plate deformations in the

Maracaibo and East Zulia Basins westem Venezuela: Marine

and Petroleum Geology vol. 14 no.

2

pp. 139-163.

2 2 K. T. and Christie-Blick N. 1985 Glossary trike-

- ~=formation asin formation and sedimentation in

. : : s . K. T. and Christie-Blick N. eds. Strike-slip

qa tio n Basin Formation and Sedimentation: Society

The authors wish to thank PDVSA and GeoQuest for the

opportunity to present this paper. Doug Crane assisted in

preparation of the illustrations.

lto

e

Ceuta

Field

Fault

Location map Alto de Ceuta

Field

Venezuela.


26/27

Memorias

Proceedings

Fig. 2 l x s e r v o i r linracterizntioriand simulatiorz workflow.

Previous

ork

Interna1PDVS

Sudies

Methodology and Work Flow

Alto de Ceuta Geologic Model Construction

Fig. Diagram of the methodology and workflow used in the construction of the Alto de Ceuta geologic model.

Geological geophysical petrophysical and reservair engineering data was integrated to produce the final geologic model.


27/27

C

Q)

Q)

O

O

Fig. 4 Genemzed Miocene nd Eocene strrtlgraphic column Alto de C e m Fieki

m

a

u

Z=

13

a

La

Rosa

Bachaquero

Laguna

Lower

Lagunillas

Marine Shale

Santa Barbara

Q)

Q)

O

O

W

Pauji

d

O

cn

S

Upper B

Lower

B

Documents

Articulos Yac de Gas