1

USE OF NUCLEAR MAGNETIC RESONANCE FOR THE RESERVOIR AND FLUID CHARACTERIZATION IN OILFIELDS OF GOLFO DE SAN JORGE

BASIN, PATAGONIA, ARGENTINA

Corbelleri, Adrián (*) – Domínguez, Hector (**) – Saavedra, Benito (**) – Sliwinsky, Leonardo (*)

(*) Vintage Oil Argentina, Inc. (**) Baker Atlas adrian.corbelleri@vintageba.com.ar hector.dominguez@bakeratlas.com benito.saavedra@bakeratlas.com Leonardo.sliwinsky@vintageba.com.ar NMR – Stimulation – Characterization – Damage – MREX Abstracto Uso de Resonancia Magnética Nuclear para la Caracterización de Reservorios y Fluidos en Campos Petrolíferos de la Cuenca del Golfo de San Jorge. Patagonia. Argentina. En enero de 2003, Vintage Oil Argentina, Inc. y Baker Atlas implementaron conjuntamente un método de evaluación de reservorios y fluidos sobre la base de tecnología de Resonancia Magnética Nuclear. El mayor objetivo de este método de trabajo fue incrementar la eficiencia en el desarrollo de campos petrolíferos ubicados en el Flanco Sur de la Cuenca del Golfo de San Jorge. Dichos campos petroleros están formados por finas capas samíticas de baja continuidad areal y en algunos casos con considerable contenido piroclástico. Producen hidrocarburos líquidos de diversa viscosidad, agua de baja salinidad y gas en diferente relación. Los cambios laterales de las propiedades petrofísicas de estos reservorios ocurren en muy cortas distancias, complicando la predicción mediante métodos convencionales de evaluación. Esta imprecisión produce una baja eficiencia durante la completación y re-completación de los pozos. A pesar de que las capas de dichos reservorios suelen ser de buena calidad petrofísica, generalmente tienen baja producción como resultado de daño producido a la formación durante las etapas de perforación, cementación y completación del pozo. Los parámetros de NMR, tales como el Volumen de Fluido Móvil (MBVM) y el Índice de Permeabilidad de Coates (Kc) son usados para proveer caracterización de calidad de roca para discriminar los reservorios, disminuir el punzado de capas secas y reducir le incertidumbre en la selección de las zonas dañadas para su estimulación hidráulica.

2

En este trabajo, se presenta los métodos de adquisición de Resonancia Magnética utilizados para determinación de fluidos, evaluación del potencial de producción de los reservorios y la optimización del programa de terminación. La preparación de una Base de Datos, organizada apropiadamente para manejar la importante cantidad de datos de NMR adquiridos por esta implementación, es una ventana para tomar nuevos proyectos de evaluación de yacimientos y contribuir a los programas de completación y re-completación de pozos. 1 - Introduction The implementation of the working method presented herein is especially targeted at increasing the efficiency in the development of the oilfields located in the South Flank of the Golfo de San Jorge Basin, to overcome one of their main hindrances: the formation damage of most reservoirs, resulting in quality petrophysical layers with poor or even no flow rate in completion testing. This method is based on a reliable characterization of reservoir petrophysical quality by means of Nuclear Magnetic Resonance (NMR) tools. As two generations of NMR technology tools: firstly MRIL-C –Magnetic Resonance Imaging Log– and then MREX –Magnetic Resonance Explorer Log– were used, their performances will be compared. The decision to stimulate a reservoir is made on the basis of its petrophysical quality, since a layer of good petrophysical properties with no traces of depletion, should yield high rates of production in the initial completion test. Otherwise, the reservoir is concluded to be affected by some formation damage that prevents the normal production of the reservoir. In this case, it is advisable to remove such damage by stimulation. In view of the preceding paragraph and for an optimum application of this reservoir evaluation method, it is paramount to add pressure data acquired by a formation tester to the NMR information. Stimulation is not advisable when poor petrophysical property beds are likely to yield low rates. Then, there are fewer chances for this kind of expensive operation to fail, as most of these fractures do not statistically record positive results. This method is highly leveraged by determining the stimulation convenience of a reservoir that, producing relatively high rates of fluid, may highly exceed its initial completion yields, were it not to have any formation damages. The NMR parameters to rank the quality of reservoirs are: the Coates Permeability Index -Kc- and the Bulk Volume Movable Index -MBVM- which enable reliable reservoir characterization, avoiding dry bed perforation and selecting the best reservoirs for hydraulic fracture stimulation. Cut-off values for petrophysical quality indexes are determined. These values will be used as a basis for reservoir discrimination. With this purpose, initial production and post-

3

stimulation flow rates from well completion and workover testing are compared with the NMR parameters corresponding to each of the tested reservoirs. This comparison of data requires a careful and detailed approach of logs and well testing information statistics. So, it is necessary to build a Database to identify variations by oilfield and by geological unit and keep it updated. This working method also intends to contribute to the identification of existing reservoir fluids on the basis of NMR information, thanks to a distinctive property of each type of fluid named diffusion. The ongoing communication between experts of the oil producer (Vintage Oil Argentina, Inc) and the oil services company (Baker Atlas) was a rewarding experience and will be advantageous for other specific issues raised in different fields of Golfo de San Jorge Basin, to implement solutions based on combined technologies. Geological Framework – Reservoir Description The Golfo de San Jorge basin is located in the center of Patagonia Argentina, partially comprising the provinces of Chubut and Santa Cruz.

This working method is applied to the oilfields operated by Vintage Oil Argentina, Inc. located in the South Flank of the Basin, and they are: Cañadón Seco, El Huemul, Meseta Espinosa, Tres Picos, Las Heras, Piedra Clavada, Cañadón León, Cañadón Minerales, Cerro Wenceslao and Cerro Overo. However, it has also been recently implemented in the Bella Vista Oeste oilfield, located in the North Flank of the Basin.

GOLFO SAN JORGE BASIN

4

In broad terms, the stratigraphic column of the Golfo de San Jorge Basin consists of a Precambrian high and low-grade and early Paleozoic granitic-metamorphic basement (Ramos, 1983, Lesta 1980). Early rift deposits, including Bahía Laura Group’s units settled in Middle Jurassic and composed of rhyolites, rhyolite porphyries and volcanic breccias, overlay. Then there are Neocomian deposits of the upper Jurassic and basal Cretaceous ages, represented by the Aguada Bandera Anticline Well Formation and the Cerro Guadal Well Formation, lacustrine and fluvial sedimentites of the late rift stage. In the Lower Cretaceous, the Well D-129 Formation is deposited. This is the quintessential source rock that has led to the production of the whole commercial oil known to date. It is constituted by organic-rich lacustrine sedimentites. In the Middle to Upper Cretaceous, the Chubut Group, where the major Basin reservoirs including those involved in this project are developed, is laid down. The Mina del Carmen Formation (South and North Flanks) described in terms of subsoil only, and its equivalent Castillo Formation (West Flank), have psammitic reservoirs with extensive tuffaceous and argillo-tuffaceous matrix. Mean porosity values range between 10 and 15%, and the permeabilities measured in core samples are up to 70 mD. In some areas, primary porosity reduction caused by siliceous and carbonaceous cementation, usually with considerable local effects (Graphic 3), has been noticed. These reservoirs also reveal

GOLFO DE SAN JORGE BASIN

5

secondary porosity attributable to fractures or micro-fissures. The mean water salinity in this formation ranges from 4 to 12 g/l. The Bajo Barreal Formation in the West Flank and its equivalents at the Center and East of the South Flank, the Cañadón Seco Formation (Caleta Olivia and O-12 Members and Cañadón Seco1 Member) and the Meseta Espinosa Formation are the main producing units of Golfo de San Jorge Basin. Mean porosities range between 15 and 20%, reaching 24% in some reservoirs of the CS1 Member and the Meseta Espinosa Formation. The mean formation water salinity values are also variable, noticing a mean increase from the reservoirs of the Caleta Olivia Member (12 - 17 g/l) to those of the CS1 Member and Meseta Espinosa Formation (22 - 25 g/l). The Comodoro Rivadavia Formation is developed in the North Flank, as the equivalent to the lower section of the Bajo Barreal Formation. Its reservoirs are made up 30 to 40% of quartz, 15 to 25 % of feldspars and plagioclases and 35 to 40% of lithics, in part with calcareous cement. The average porosity is 18-19% with a permeability of 75 mD. In this Flank, the Upper Cretaceous comes to an end with deposits of El Trébol Formation, equivalent to the Meseta Espinosa Formation and the upper section of the Bajo Barreal Formation. The origin of sandstones, constituents of most of the reservoirs involved in this project, is associated with the volcanic phenomena taking place throughout the evolution of the basin. Therefore the matrix, largely found in these reservoirs, leads to low porosity and high variability of matrix density values. In a study on Nuclear Magnetic Resonance application in the South and North Flanks of the Basin, the matrix density values achieved range between 2.43 g/cm3 and 2.71 g/cm3. This variation of the matrix density affects the porosity determination of density logs, accounting for the application of porosity tools, such as the Nuclear Magnetic Resonance, regardless of the type of reservoir rock. The main clay minerals contained in the reservoirs are: montmorillonite, illite and kaolinite. The ratio of any of these clay mineral groups varies considerably, recording different values when measured with neutron or density tools. Density tools are also affected by isomorphic substitution. The low primary porosity of reservoirs brought about by the prevalence of argillo-tuffaceous matrix is even more pronounced by the alteration of feldspars or lithics to kaolinite because of diagenesis. Smectite, also formed by diagenesis, blocks the pore throats of the reservoir, decreasing its permeability by obstructing the connected porosity. The variability of formation water salinity is typical of the Golfo de San Jorge Basin. As this variation is areal as well as vertical, it is hard to interpret the type of existing reservoir fluid in terms of the data acquired by resistivity tools. This issue is even more concerning in some reservoirs because laminar claystones lead to the acquisition of low horizontal resistivity values as a consequence of resistive anisotropies. As the fluid diagnosis reached

6

with NMR data depends on properties other than resistivity, it becomes an excellent choice to improve the evaluation of producing reservoirs. 3- Reservoir Characterization with NMR The low porosity and large number of small pores for the high content of argillo-tuffaceous matrix, typical of most reservoirs of the Basin, entails high irreducible water saturation, which significantly decreases the overall leverage of effective reservoir porosity. As a result, the layer will only produce those fluids not adhered to the pore walls by capillary pressures. Thus, high effective porosity rocks with high irreducible fluid volume are usually reservoirs of less petrophysical quality than those of less effective porosity with low irreducible fluid volume. Given that the Bulk Volume Movable Index -MBVM- and the Coates Permeability Index -Kc- clearly indicate the producible fluid volume, this kind of technology is virtually irreplaceable in the Basin, as enables a more precise recognition of reservoir quality than any other porosity tool. As the reservoir effective porosity is directly measured by NMR tools, the volume of irreducible fluid must be correctly defined in order to get a reliable Volume Movable Index that determines the quality of reservoirs. This poses an interesting challenge, since in several operations performed in the Golfo de San Jorge Basin, the variability of T2 cut-off to be applied to get such parameter has been clearly established. Characterization is even more difficult because there are several heterogeneous reservoirs that are different from each other in the column crossed by each well. Together with this working method, a continuing thirty-three-millisecond T2 cut-off is used for all cases. Then a cut-off value of the quality petrophysical parameter for every oilfield and geological unit is defined by comparing the NMR parameter value with the rate yielded by the reservoir in well testing. So reservoir responses are compared with data of the kind but from different extraction: NMR log data with a vertical resolution of about 5 feet (1.5 meters) with reservoir flow rate testing of 3.3 to 9.8 feet (1 to 3 meters) of average thickness. This method ensures a more accurate reservoir characterization than that resulting from the comparison of log information with specific analysis data. At the onset of the process, the boundary values used are the Basin averages, which are then adjusted with new data acquired as the fields are developed. 4- Determination of Boundary Values for Petrophysical Quality Indexes The process to determine the boundary values for NMR parameters showing the quality of the reservoir, is based on a comparative analysis of such indexes vis-à-vis the initial and post-fracture flow rates acquired during the completion and workover testing of each of the analyzed reservoirs.

7

In these bar charts, it is quite simple to establish when a reservoir should and when should not produce high flow volumes. As it is feasible to identify good quality petrophysical reservoirs that have been damaged, producing, consequently, flow volumes that are not consistent with their true capacity, by facilitating the selection of beds that could be stimulated by hydraulic fracturing to remove such damage (please refer to the detail of the chart above). The following table summarizes the cut-off values established for each oilfield where this working method was applied. Such analysis was carried out by Geological Unit when the amount of data was sufficed.

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

10000

Cau

dal (

l/h)

1.8 3.9 4.6 5.0 5.2 5.4 5.7 5.8 6.1 6.3 6.6 7.1 7.4 7.6 7.8 8.1 8.3 8.5 8.9 9.2 9.8 10.2 10.6 11.6 12.2 14.9MBVM

Yacimiento Cañadón SecoIndice de Fluido Movil (MBVM) vs Caudal Inicial y Post-Fractura

Caudal Inicial Caudal Post-Fractura Initial Volume Post-Fracture Volume

Cañadón Seco Oilfield Bulk Volume Movable Index (MBVM) vs. Initial and Post-Fracture Volumes

Volu

me

(l/hr

)

0

1000

2000

3000

4000

5000

6.1 6.1 6.1 6.1 6.1 6.1 6.1 6.2

8

Petrophysical Quality Indexes Table (by Oilfield and Geological Unit)

PETROPHYSICAL QUALITY INDEX OILFIELD WELLS BEDS GEOLOGICAL UNIT

Kc MBVM GENERAL 1.7 5.7 FM. MESETA ESPINOSA 3.1 6.4 MBO. CS1 2.2 5.8 MBO. CALETA OLIVIA 2 6

CAÑADÓN LEÓN 27 233

FM. MINA DEL CARMEN 1.7 5.7 GENERAL 2.4 6 FM. MESETA ESPINOSA - - MBO. CS1 - - MBO. CALETA OLIVIA - -

CANADÓN MINERALES 10 77

FM. MINA DEL CARMEN 2.4 6 GENERAL 1.0 4.9 FM. MESETA ESPINOSA - - MBO. CS1 - - MBO. CALETA OLIVIA 1.4 5.3

CANADÓN SECO 27 484

FM. MINA DEL CARMEN 1.0 4.9 GENERAL 1.4 5.3 FM. MESETA ESPINOSA - - MBO. CS1 2 5.6 MBO. CALETA OLIVIA 1.5 5.3

MESETA ESPINOSA 23 367

FM. MINA DEL CARMEN 1.4 5.3 GENERAL 1.2 5 FM. MESETA ESPINOSA - - MBO. CS1 1.6 5.4 MBO. CALETA OLIVIA 1.4 5.2

EL HUEMUL 29 315

FM. MINA DEL CARMEN 1.2 5 GENERAL 1.3 5.2 FM. MESETA ESPINOSA - - MBO. CS1 - - MBO. CALETA OLIVIA 1.3 5.3

TRES PICOS 15 213

FM. MINA DEL CARMEN 1.3 5.2 GENERAL 1.1 5.1 FM. BAJO BARREAL 1.1 5.1 LAS HERAS / PIEDRA CLAVADA 36 392 FM. CASTILLO 1.8 5.7 GENERAL 1.2 5.2 FM. BAJO BARREAL 1.2 5.2 CERRO WENCESLAO 9 110 FM. CASTILLO - - GENERAL - - FM. MESETA ESPINOSA - - MBO. CS1 - - MBO. CALETA OLIVIA - -

CERRO OVERO 2 15

FM. MINA DEL CARMEN - -

TOTAL 177

2159

In order to implement this working method effectively, it is paramount to build and update a database enabling the statistic treatment of information derived from the NMR, other open hole logs, flow volumes and types of fluids produced during well completion and/or workover testing. 5- Database The Database is built on the basis of tables for each well. Thanks to the fact that since November 2002 NMR data have been acquired in all of the 177 drilled wells and 2,159 beds have been evaluated, it has been feasible to build a reliable Database with extensive pieces of information that provide statistic soundness.

9

This kind of Database is helpful to determine cut-offs for petrophysical quality parameters. It has also facilitated the analysis of aspects related to reservoir producing potential through the MH and KH parameters, resulting respectively from the rock quality indexes MBVM and Kc in the bed thickness, with a MBVM index higher than the cut-off value corresponding to the field. On account of the statistic comparison of production rates with rock quality data, progress has been made on the awareness and control on how and to what extent reservoirs are damaged in the well drilling stage. This information is correlated with the radiuses of invasion determined by the HDIL -High Definition Induction Log- tool inversion processing data and the existing clay groups of the reservoirs determined by Spectral Gamma Ray SL –Spectra Log– tool and its respective calibration through laboratory analysis. The existing interaction between the different types of drilling mud and reservoir responses during completion and/or workover testing, is taking advantage of to define the type and properties of the most suitable mud for each oilfield. Recently, pore-size distribution defined by T2 distribution was used to design mud in terms of predominant pore sizes with the purpose of minimizing formation damages in the drilling stage. 6- Fluid Characterization The identification of the type of existing reservoir fluids is provided by means of a distinctive property of each type of fluid named diffusion, which is produced by a further decline of echoes facing a gradational magnetic field, affecting low viscosity fluids to a greater extent. This property can be leveraged in order to separate NMR signals coming from water of those coming from oil, given the different diffusion constants of both fluids. In order to make use of the diffusion property of fluids in well logging, it is necessary to carry out a multiple acquisition with different timing between echoes (TE), considering that T2 depends on TE2. During the implementation of this working method, an NMR technology, MRIL-C –Magnetic Resonance Imaging Log- was upgraded by MREX –Magnetic Resonance Explorer Log–. With any of them, it is just necessary to visually compare the T2 spectra acquired with different TE in a gradational magnetic field to define the type of existing reservoir fluid, taking into consideration characterizations such as those that will be exposed in the following plots, which were adjusted in line with the progress of the Project. In the case of the MRIL-C the fluid prediction was based on the Dual TE data acquisition, with which two T2 spectra are acquired: one with a 1.2 m TE and other with a 2.4 m TE. When the existing reservoir fluid is Oil, both spectra are virtually equal. The T2 spectrum corresponding to the 2.4 m TE (located on the right of the chart) is not to be shifted to the

10

left of the 1.2 m TE (spectrum located on the left). This happens because of the poor diffusion of this type of fluid.

Sample of MRIL-C log in an Oil-bearing Reservoir As water has more diffusion, when it is contained in the reservoir, the spectrum on the right will show a shift to the left as to the 1.2 TE, as can noticed in the following plot.

Sample of MRIL-C log in Water-bearing Reservoir

Viscous oil has a lower T2 than medium oil (T2 similar to that of water). Nevertheless, as viscous oil has also low diffusion, it will be identifiable for the lack of relative shift of both spectra.

Sample of MRIL-C log in Viscous Oil-bearing Reservoir

MPHE MBVI

T2 Distribution Kc IndexTE: 2.4 ms

T2 Spectra

TE: 1.2 ms

MBVM Index

SP

MPHE MBVI

T2 Distribution Kc IndexTE: 2.4 ms

T2 Spectra

TE: 1.2 ms

MBVM Index

SP

MPHE MBVI

T2 Distribution

deKc IndexTE: 2.4 msTE: 1.2 ms

T2 Spectra MBVM Index

SP

11

Other resource employed for oil diagnostic that leverages diffusion effects is the T2 max water value, which depends on the acquisition parameters, temperature and water viscosity. This maximum value is shown on the log by a blue line in the T2 spectrum corresponding to the 2.4 m TE. Every signal above this line is driven by the oil of the area being read by the tool. As there is a significant contrast between the gas diffusion constant and those of other fluids, this property could have been used to identify it. But the low gas pressure of our reservoirs cause a low volume of associated hydrogen, resulting in a very blurred signal usually camouflaged by the strong one of high irreducible water saturations, typical of this Basin. The MREX (MR Explorer) is a new generation technology that operates with different frequencies and multiple field gradients. A multiple-frequency operation allows continuing data acquisition without dead time for polarization recovery. Multiple field gradients are crucial for any hydrocarbon typing based on diffusion. Additionally, acquisition pre-planning was replaced by the Objective-Oriented Acquisition (OOA) method consisting of four pulse sequence packages that meet all NMR log requirements. These packages are PorePerm, PorePerm + Oil, PorePerm + Gas and PorePerm + Heavy Oil. The new Magnetic Resonance tool MREX is run on the acquisition PorePerm+Oil mode, providing three T2 spectra corresponding to simultaneous recording performed with different GTEs (product of the Magnetic Field Gradient and the TE used), two sequences of Double Time of Wait (DTW) and a T1 spectrum, providing precise fluid predictions in terms of a characterization based on the interaction of the three T2 spectra, interpretation software and the T2 and T1 spectra-relation analysis. The direct fluid determination in terms of the three T2 spectra acquired with different GTEs, also takes advantage of diffusion, the fluid property, by separating NMR signals coming from water of those from oil, because of the different diffusion constants of both fluids. When the existing reservoir fluid is Oil, the three spectra should be virtually equal for the low diffusion of this type of fluid.

Sample of MREX in Oil-bearing Reservoir

12

As water has more diffusion, when water is the reservoir fluid, both spectra on the right will show a shift to the left as to that of lower GTE, as it is shown in the following chart.

Sample of MREX in Water-bearing Reservoir

The water T2max is also used to determine the type of fluid and appears with two blue lines in the three T2 spectra in the MREX log. Every signal above these lines is made by the oil of the area read by the tool. The application of different MRLab software modules specifically developed to process and interpret the extensive amount of information acquired, enables the acquisition of differentiated fluid spectra, hydrocarbon volumes and viscosities of the area measured by the tool. In the two preceding plots the

13

differentiated water and oil spectra acquired by the SIMET processing module, through a

simultaneous inversion processing of multiple echo trains are shown. This is an effective means of predicting the type of existing reservoir fluid, as it is shown in the statistic analysis results of the following table. 7- MRIL-C and MREX Performances The introduction of the latest generation tool MREX –Magnetic Resonance Explorer Log– entailed significant operating enhancements to the Project, optimizing the quality and quantity of acquired information and decreasing logging time by 23%. In both cases, the NMR tools ran in a single pass with: HDIL (High Definition Induction Log) – Caliper – GR and DAL (Digital Acoustic Log). Data acquisition with MRIL-C –Magnetic Resonance Imaging Log– was performed in Dual TE –DTE– mode, acquiring the following information in a single logging pass (logging velocity: 3.5 m/min or 11.5 feet/min): - Effective Porosity– MPHE – - Bulk Volume Irreducible – MBVI- - Bulk Volume Movable– MBVM - Coates Permeability Index – Kc - T2 Distribution - 2 T2 spectra acquired with different TE – DTE –

OILFIELD NUMBER OF WELLS

NUMBER OF BEDS EFFECTIVENESS

CAÑADÓN LEÓN 25 208 82.04%

CANADÓN MINERALES 10 77 74.60% CANADÓN SECO 25 458 83.63%

MESETA ESPINOSA 23 366 87.34% EL HUEMUL 28 301 81.04%

TRES PICOS 15 213 80.84%

LAS HERAS / PIEDRA CLAVADA 35 380 81.72%

CERRO WENCESLAO 7 83 93.33%

CERRO OVERO 2 15 81.82%

TOTAL AVERAGE 168 2086 83.07%

14

MREX data acquisition in Fast PorePerm+Oil mode, sequence specially designed for the Golfo de San Jorge Basin, allows the acquisition of the following information in a single logging pass (logging velocity: 4.5 meters/min or 14.7 feet/min): - Total Porosity– MPHS – - Effective Porosity– MPHE – - Bulk Volume Irreducible – MBVI – - Bulk Volume Movable – MBVM – - Coates Permeability Index – Kc – - T2 Distribution -3 T2 spectra acquired with different GTEs - 2 Double Time of Wait sequences – DTW – The mentioned 23% operating time enhancement is even greater if we consider that in order to acquired by MRIL-C all the information acquired by MREX, three passes are to be run. Regarding fluid predictions made with both services, the mean MRIL-C effectiveness was 78% before performing with MREX. As it can be noticed in the following bar chart, both technologies coexisted for three months until the total replacement occurred. When MREX started to perform, there was a remarkable increase of effective fluid predictions, reaching 83% at the time of drafting this paper. 7- Reservoir Stimulation through Hydraulic Fractures The major goal of the implementation of this working method was the optimization of the development of oilfields affected by formation damages as a common problem. The reservoir evaluation performed on the basis of NMR information, allows the accurate identification of good petrophysical quality reservoirs, layers that if, due formation damage, yield low flow rates during well completion and/or workover testing, are stimulated by hydraulic fractures to remove the formation damage.

15

The application of the evaluation and correction method presented for this problem affecting the productivity of oilfields involved in this Project, has proved to be very favorable by contributing to the

75.00%

76.00%

77.00%

78.00%

79.00%

80.00%

81.00%

82.00%

83.00%

84.00%

ENERO MARZO MAYO JULIO SETIEMBRE DICIEMBRE FEBRERO

ACIERTOS

MRIL

MREX

JANUARY MARCH MAY JULY SEPTEMBER DECEMBER FEBRUARY

EFFECTIVENESS

Monthly Oil ProductionDrilling Activity and Number of Hydraulic Fractures

0

20000

40000

60000

80000

100000

120000

140000

160000

180000

Sep-02 Nov-02 Jan-03 Mar-03 May-

03 Jul-03 Sep-03 Nov-03

Jan-04 Mar-04

May-04 Jul- Sep-04 Nov-04 Jan-05 Mar-05

0

5

10

15

20

25

30

35

40

45

Hydraulics Fractures

Monthly Oil Production

1 Rig 2 Rigs 3 Rigs 4 Rigs

5 Rigs

m3/mes

16

remarkable production increase, verified as soon as the implementation kicked off, as can be noticed in the chart above. It is worth mentioning that many factors contribute directly to the over all production of the fields, there is a strong link between the turning point of the monthly oil pay curve and the use of hydraulic stimulation as a regular optimization tool. Therefore, it is evident that this working method played a major role in the substantial increase achieved. 8 - Conclusions

- The success achieved by the working method jointly implemented by both Companies, has allowed to significantly optimize the development of oilfields operated by Vintage Oil Argentina, Inc. in the South Flank of the Golfo de San Jorge Basin.

- Based on a reliable reservoir quality characterization, hydraulic fracture stimulation

was implemented in those reservoirs of good petrophysical quality that underproduced by reason of formation damages.

- The determination of cut-offs for the two petrophysical quality indexes, has allowed

to minimize the uncertainty in the selection of layers to be stimulated by hydraulic fracturing, optimizing the investment made in this kind of operations.

- The good performance of fluid predictions has allowed to minimize the perforation

of water-bearing beds and ensure perforation of low-resistivity producing layers.

- The use of a well-organized Database enables the monitoring and evaluation of the formation damage inflicted to reservoirs while drilling and the analysis of the potential of those reservoirs, wells and oilfields where this working method is being implemented.

- With the excellent operating performance of MREX, the logging time was

optimized considerably, reducing related costs.

8 - Acknowledgements The authors acknowledge Vintage Oil Argentina, Inc. and Baker Atlas for authorizing the publication of this paper, and want to thanks the contribution of Sergio Giordano, Enrique Feinstein and Nestor Navarrete from Vintage Oil Argentina, Inc.

17

9 - References S. Chen, D. Beard, M. Guillen, S. Fang and G. Zhang: MR Explorer Log Acquisition Methods: Petrophysical-Objective Oriented Approaches, SPWLA 44th Annual Logging Symposium, June 22-25, 2003 S. Chen, D. Beard, M. Guillen, S. Fang and G. Zhang: G.TE Correction for Processing Multigradient, Multiple –TE NMR Log Data. SPE 84481 Rocas Reservorio de las Cuencas Productivas de la Argentina, V Congreso de Exploración y desarrollo de Hidrocarburos, Mar del Plata, 2002. S. Chen, C.M. Edwards, and H.F. Thern. Western Atlas Logging Services. Advances in NMR Log Processing and Interpretation Delia C. Diaz, Eduardo Breda, YPF, S.A. Comodoro Rivadavia , Argentina, Carlos Minetto, Baker Atlas, Comodoro Rivadavia, Argentina, Songhua Chen, SPE, Baker Atlas, Houston, USA. SPE 56425 Use of NMR Logging for Formation Damage Prevention: Water-Flooding Case Study in Cañadón Seco, San Jorge Basin Songhua Chen, SPE, Western Atlas Logging Services, Houston, USA; Oscar Olima, YPF S. A., Héctor Gamín YPF S.A.,Comodoro Rivadavia, Argentina; Daniel T. Georgi, SPE, Western Atlas Logging Services, Houston, USA; J. Carlos Minetto, Western Atlas Logging Services, Comodoro Rivadavia, Argentina SPE 49009 Estimation of Hydrocarbon Viscosity with Multiple TE Dual Wait-Time MRIL Logs M. Altunbay, C.M. Edwards and D.T. Georgi, Western Atlas Logging Services SPE 38027 Reducing Uncertainty in Reservoir Description with NMR-Log Data