advances in formation evaluation independent of conveyance method

SPWLA 53rd Annual Logging Symposium, June 16-20, 2012

1

ADVANCES IN FORMATION EVALUATION INDEPENDENT OF CONVEYANCE METHOD: STATE OF THE ART LOGGING WHILE

DRILLING & WIRELINE PETROPHYSICAL ANALYSIS IN A CARBONATE RESERVOIR OFFSHORE BRAZIL

P. Ferraris, I. Borovskaya, Schlumberger, M. Ribeiro, OGX

Copyright 2012, held jointly by the Society of Petrophysicists and Well Log Analysts (SPWLA) and the submitting authors This paper was prepared for presentation at the SPWLA 53rd Annual Logging Symposium held in Cartagena, Colombia, June 16-20, 2012. ABSTRACT Recent wells drilled by an operator offshore Brazil provided the opportunity to perform a direct comparison of multi-mineral formation evaluation using as input either traditional Wireline (WL) or Logging While Drilling (LWD) data. The principal target was an Albian carbonate reservoir of the Quissamã Formation. This formation has a complex lithology with variable amounts of dolomitization and presence of quartz and clay. Computing a correct matrix density and characterizing the rock texture for producibility estimation is critical. Initially a 12.25 inch diameter vertical pilot well was drilled with Synthetic Oil Based Mud (SOBM) and logged using basic LWD tools (resistivity / density / neutron). A complete WL program followed for a better understanding of reservoir characteristics. The logging program included induction, neutron-density, nuclear magnetic resonance (NMR), elemental spectroscopy, formation pressure measurements and fluid samples. In spite of unknown formation water salinity it was relatively straight forward to identify a formation water resistivity value consistent with log responses over the lower reservoir section. Resistive invasion patterns clearly indicated the permeable intervals below the free water level, confirmed by the NMR T2 distribution profile. Pressure gradients and fluid samples demonstrated the validity of the analysis. In order to explore reservoir connectivity and facies variation at some distance from the vertical hole the pilot well was side-tracked using an “S” shape trajectory with a maximum inclination of 55 degrees. The side-track borehole was drilled with an 8.5 inch bit size with the same type of SOBM, using a BHA which included rotary steering assembly, multi-function measurement tool and LWD NMR tool. The LWD measurements allowed the formation evaluation analysis performed in the pilot well to be replicated.

Capture cross-section (or Sigma) may be sensitive to the invaded zone due to its shallow depth of investigation, while 2 MHz resistivities read far beyond. Use of Sigma measurement in place of the WL shallowest induction resistivity for flushed zone analysis proved to be an effective alternative. A porosity partitioning methodology enabled textural analysis using WL & LWD NMR data. Rock type classification provided the relative fractions of micro, meso and macro porosities. Side-track data compared to the pilot well showed facies changes with additional dolomitization but not the expected increase in porosity. Lithology patterns were recognized over specific intervals validating the consistency of the WL and LWD spectroscopy. LWD data quality benefitted from the improved statistics of the measurements permitted by the slow drilling rate in carbonates. The results confirmed that when WL acquisition is either not possible or not economically viable, LWD measurements under the proper drilling conditions provide equally effective data for a consistent petrophysical analysis. The LWD data proved to be reliable and demonstrated the potential to spare extra investigation costs. INTRODUCTION A Brazil offshore operator is currently developing a post salt carbonate reservoir using pilot and horizontal wells. Pilot wells are drilled for target identification and initial formation evaluation. The information obtained provides reduced depth uncertainties, fluid gradients, fluid contact identification and help establish references for possible further exploration using deviated, high-angle or horizontal wells.

As is common practice, the main petrophysical evaluation in low angle pilot wells is performed using traditional wireline measurements. In high angle wells, due to conveyance difficulties either LWD or combinations of WL and LWD logs are used. It is vitally important to understand the applicability and


2

limitations of the measurements available from the two conveyance systems.

Interchanging measurements acquired by the most practical or financially advantageous method in theory should occur without quality compromises. Carbonate reservoirs have specific petrophysical evaluation challenges that complicate analysis of the reservoir. Storage and flow potential depend on the original rock deposition, mineral composition and overall diagenesis. Correct identification of these properties requires an appropriate choice of logging measurements, that should be made early in the development stage to guarantee optimum well placement and reservoir evaluation. Traditional sets of measurements are often not sufficient to provide a comprehensive answer in such environments. Inclusion of spectroscopy (for mineralogical analysis) and NMR (for texture classification) provide reduced uncertainty.

Documenting this process and the implications of the technology used is the objective of this paper, developing on previous work published by Ribeiro, Ferraris and others in OTC paper 22738.

GEOLOGY OVERVIEW AND RESERVOIR DESCRIPTION The Quissamã Formation (Macaé Group) reservoir, which is the target of this study, consists of carbonate rocks deposited during the Albian (Upper Cretaceous) age. It is part of the Campos Basin, located in the Rio de Janeiro continental shelf, southeastern offshore Brazil. The reservoir interval is partially dolomitized in its lower half with shoaling upward cycles from matrix to grain-supported rocks. In its upper part the reservoir is mainly composed of beds of grain-supported limestone with secondary siliciclastic richer intervals. The average porosity is 15 p.u., occasionally reaching 25 p.u.. Cores and electric/ultrasonic image logs allow identification of closed fractures and oil-bearing open fractures. Calcilutites and marls of the Outeiro Member overlay this zone. PILOT WELL ANALYSIS A 12.25 inch diameter vertical pilot well reaching the formation target was drilled with Synthetic Oil Based Mud (SOBM) and a minimal set of LWD services (2 Mhz resistivity, stabilized density and neutron). Subsequently a complete Wireline logging program was executed. The WL logging program included induction resistivity, neutron-density, nuclear magnetic resonance (NMR), elemental spectroscopy, formation pressure measurements and fluid samples. LWD data was depth matched to the WL logs. It is worth noting that the WL & LWD logs matched at TD but required depth shifting

along the open hole section following changes in formation stiffness (affecting drilling) or changes in cable tension (affecting wireline data). The depth difference varied between minus 0.5 and plus 3.4 m MD along the open hole section. Near the casing shoe, only a small depth difference was observed. These findings prove that both raw depth measurements have a relative amount of inaccuracy, generally ignored but highlighted when a comparison is possible. Further depth refinement is possible using modeling but this is not the principal focus of this paper. WL logs were taken as depth reference in the pilot well.

Figure 1 shows a snapshot of LWD composite logs over the carbonate reservoir section. SOBM mud was used to minimize drilling related problems. The invasion was relatively shallow as indicated by the lack of separation between the LWD resistivity curves. Consequently, resistivities could not identify movable fluids.

Figure 1: Basic Logging While Drilling composite log.

Figure 2 displays the results of a basic multi-mineral petrophysical analysis driven by gamma ray, photoelectric factor (PEF), bulk density, thermal neutron porosity and deep resistivity. As the LWD measurements were acquired before significant invasion had occurred, flushed and un-flushed zone saturations were constrained to be the same. All measured logs were overlaid by reconstructed curves, with the exception of PEF, which was slightly boosted by a small fraction of barite in the mud. In spite of quartz and dolomite being a part of the model, the available logs could not identify any significant fraction of these components. It is interesting to note that in this

50 m


3

well the computed porosity from LWD basic analysis resulted in practically equivalent porosity values to those derived from an extensive evaluation using the WL spectroscopy-driven matrix composition, which is discussed later in this paper.

Figure 2: Basic Petrophysical Interpretation using LWD logs

POR_QE (Quanti-ELAN* porosity output) reconstructed from a simple LWD data analysis, and a curve derived using the full evaluation from WL data overlay indicating excellent agreement. The second track from the right in Figure 2 and Figure 3 provide confirmation.

Figure 3: Comparison between LWD derived porosity (Y axis) and

WL derived porosity (X axis)

Finally, Sw from LWD and WL analyses also proved to be very close as shown in the right track of Figure 2.

The quality of reservoir and a clear identification of movable fluids cannot be seen on Figure 2 as the information is not available from the basic set of measurements used in the analysis. In this formation, Net Pay may be underestimated if based on water saturation alone. However, high water saturation does not always imply water production. In presence of a large fraction of micro-porosity, capillary forces may prevent water trapped in the small pores from flowing. The WL logging program in the pilot well included NMR data to identify the bound water volumes. T2 distribution measurement analysis allows non-movable fluid to be distinguished from free fluid.

Laboratory measurements by Boyd et al (2011) confirmed that the methodology used in Water Based Mud could be extended to SOBM when light hydrocarbons are present. In these conditions, surface relaxation is predominant and the shape of the T2 distribution still reflects the texture of the rock.

Figure 4 is a snapshot of the input channels used in the WL petrophysical interpretation. The six elemental dry weight fractions define the rock matrix mineralogy. To differentiate between calcite and dolomite, elemental capture spectroscopy data were processed using the MgWALK closure model with magnesium among the input yields. To provide sufficient statistical information, the logging speed did not exceed 60 m/hr. Induction resistivity data showed predominantly resistive invasion and was processed using a 1-D radial inversion to extract Rxo and Rt. Density and neutron porosity measurements were used for porosity computation. Neutron porosity was corrected for all environmental effects ecept formation water salinity, which is handled within the ELAN* solver. The NMR bound fluid channel was assigned to the irreducible water volume.

Figure 4: Selection of WL input logs for Petrophysical Analysis

50 m

LWD derived porosity vs WL derived porosity


4

Use of total NMR porosity (TCMR) is optional and two approaches are possible:

i. TCMR is not included in the input equations. It is used post-analysis for a consistency check by overlaying computed porosity with lithology independent NMR porosity.

ii. TCMR is included in the solver, contributing

directly to the porosity estimation and reflecting its consistency with the analysis and other measurements in the reconstructed curves overlay.

Figure 5 illustrates parameter initialization in the ELAN solver. It is useful to comment on the logic used for documentation purpose. The input properties window (Figure 5 upper panel) contains log uncertainties normalized to 1.5 equivalent porosity units. Optionally the user may alter their relative weight (in this case, they were maintained constant at one). The un-flushed factor determines if a given log affects the flushed zone (X) or un-flushed (U) zone analysis. Red entries are the average values of variables dependent on temperature and pressure, initialized previously.

The component specification table (Figure 5 second panel) demonstrates the list of minerals and fluids in the model being solved. Elemental dry weight end-points documented in the literature (Herron 1996) are default values loaded automatically from the database. Formation water is split into UWater (uninvaded zone formation water which is free to flow), UIWater (uninvaded zone irreducible water), XWater (flushed zone free water) and XIWater (flushed zone irreducible water). Drilling with SOBM determines that the mud filtrate is only oil. This simplifies the analysis, as XWater has the same characteristics (salinity) as UWater. In addition, the irreducible volumes of water in the flushed and unflushed zones are taken to be numerically the same. A constant tool handles this condition as specified in the additional constraints tab (Figure 5 lower panel). The sum of this irreducible water and the volume of the clay bound water associated with Illite was set equal to the bound fluid volume measured by NMR

The dual water saturation equation was chosen for both invaded and uninvaded zones. NPHU was selected as a non-linear neutron equation for consistency with the type of neutron porosity chosen for input.

Formation salinity was not initially known for this part of the reservoir. A reservoir zone believed to be below

the free water level was chosen for ELAN* analysis. The value of formation water salinity was iteratively changed until the apparent water resistivity matched the Rt curve over that zone.

Figure 6 displays the quality control layout of the multi-mineral analysis. On the left the relevant WL input logs and their corresponding reconstruction are displayed. In this well magnesium, sulfur and iron dry weight fractions are rather small, indicating that the amount of diagenesis and heavy minerals is limited. The methodology applied in this case can be extended to other complex cases already encountered in the same region. Density, neutron, and NMR total and bound fluid porosities reconstruct well within the uncertainty bands for each input curve, supporting the validity of the analysis.

Three intervals are numbered on the log, highlighting intervals of particular interest.

A shallower interval identified with number “1” and green rectangle is a zone with low Sw. All the water is irreducible. This zone is a good target to land a horizontal well since over this interval no water will be produced.

The next interval, identified with number “2” and a black rectangle, is a zone with high water saturation. Logs based on independent physical measurements show remarkable consistency. Rxo and Rt overlay, indicating a lack of permeability. The computed water volumes appear to represent irreducible water. The combination of these two indications suggests that this interval is a tight zone, with very low permeability and no movable fluid. In spite of high Sw values, no water will be produced from this zone.

The interval identified by the number “3” and a blue rectangle is a zone with low Sxo and high Sw (close to 100%). Over this section, mud filtrate has displaced original formation water. Resistivity logs show resistive invasion and the total amount of water is larger than the volume of bound fluid. This condition is characteristic of a permeable water zone invaded by oil filtrate. The flushed zone analysis indicates that all the movable water was replaced by oil based mud filtrate.

The third track from the right displays the result of Quanti-ELAN* porosity evaluation compared to NMR porosity. The two curves overlay demonstrating good agreement between the NMR data and other logs, confirming that environmental corrections were properly applied and NMR porosity provides a good measurement of lithology- independent porosity.


5

Input Properties

Component Specifications

Special Models

Additional Constraints

Figure 5: Petrophysical analysis parameter initialization.

Textural analysis assists in permeability estimation. In carbonates it is important to characterize pore size and the way they are interconnected, in addition to the absolute value of total porosity. NMR T2 distribution shape can be related to pore size distribution. In predominantly cemented carbonates (mudstone) the pores have similar size and the resultant T2 distribution for a single saturating fluid is narrow. The more the texture evolves from mud-supported to grain-supported (wackstone–packstone–grainstone facies evolution) the T2 distribution gets wider, exhibiting a longer tail towards large T2 values.

Empirical correspondence between NMR T2 distribution shape and actual facies described on cores has been was demonstrated in several papers describing Middle-East carbonates. Although the origin of the Brazil carbonates is more complex and heterogeneous than the ones in Middle East, the texture classification principles still stand. Using a second cutoff to separate meso- from macro-porosity, it is possible to separate the three porosity components (micro, meso, macro).

Figure 7 shows the results of NMR based textural analysis. From left to right the following information is displayed:


6

Figure 6: Multi-mineral evaluation using wireline data

Figure 7: Textural analysis with NMR data

1. Multi-mineral petrophysics evaluation (Quanti-ELAN* results)

2. NMR T2 distribution with micro-meso and meso-macro cutoffs


7

3. Permeability estimation using porosity partitioning method compared to MDT mobilities measured in the same well

4. NMR porosity split in micro-meso-macro fractions

5. Rock texture modulated by the best carbonate permeability estimation

6. Water saturation computed using the saturation height function derived from Free Water Level (FWL) and capillary pressure transform computed from NMR T2 distribution

7. Irreducible water volumes from saturation height function (SHF) and multi-mineral analysis. The two methods demonstrated good agreement.

8. Capillary pressure obtained from T2 distribution integration

Figure 8 shows the result of MDT pressure station interpretation. Gradients in water and oil zones were computed after excluding pressure data with variable degrees of supercharging. The location of the FWL was compatible with petrophysical interpretation and in agreement with SHF modeling.

Figure 8: Gradient and FWL computation Two fluid samples and one optical fluid analysis identification were acquired over the carbonate section of this well. The results are displayed in figure 7: the shallowest station was an oil sample. The second station from the top also identified oil and the lower station sampled mostly water. These results validated the predictions based on logs and gradient measurements, providing further verification of the analysis. HIGH ANGLE WELL ANALYSIS In order to explore reservoir connectivity and facies variation at some distance from the vertical hole the pilot well was side-tracked using an “S” shape trajectory with a maximum tangent inclination of 55

degrees before dropping to 49.7 deg at the base of the reservoir. The 8.5 inch bit size side-track borehole was drilled with the same type of SOBM as the pilot hole using a BHA which included Rotary Steering Assembly, multi-function measurement tool and LWD NMR tool. The measurements acquired on the sidetrack well were propagation resistivity, neutron-density, elemental spectroscopy, NMR, and Sigma. The measurements have different azimuthal sensitivities and so are sensitive to different regions of the formation around the borehole. Propagation resistivity, the measurement with the deepest depth of investigation, normally reads beyond the flushed zone, while Sigma, the shallowest volumetric measurement, is used to characterize the flushed zone. Due to the relatively small time after bit, the resistivity logs have no visible separation suggesting negligible invasion. In addition, the well inclination over the reservoir section was not excessively high and therefore did not trigger 2D effects like polarization horns. For this reason, P40H was assumed to represent Rt. Use of the sigma measurement in place of the shallowest WL induction resistivity for flushed zone analysis proved to be an effective alternative and was chosen to perform the analysis. Spectroscopy measurements for the carbonate zone detected mostly calcite with inclusions of dolomite, in larger proportion than for the WL logs. Quartz and clay are also present in the formation. NMR response was good, reading within the invaded zone. It responded mainly to surface relaxation enabling rock texture characterization. Figure 9 shows the list of LWD channels available for petrophysical analysis. This list is directly comparable to the one displayed on Figure 4 for the pilot well where WL logs were used instead. Apart from measurement name differences, the quintessence of the measurements is equivalent. The main differences were density orientation and sigma. The best LWD density in deviated holes is the bottom quadrant. The physics of measurement is very similar to the density pad measurement of the WL tool. As mentioned earlier, due to the shallow invasion at LWD time, sigma was used for flushed zone analysis instead of Rxo.

Water gradient: 1.xx g/cm3

Oil gradient: 0.xx g/cm3


8

Figure 9: Selection of LWD input logs for Petrophysical Analysis

The equivalence between WL and LWD logs has a practical advantage of allowing a replication of the methodology used in the pilot well for the side-track well.

The Quanti-ELAN* solver was setup similarly, requiring only a swap of one equation, as shown in Figure 10. A good reconstruction of the logs using the modeled responses was achieved without requiring any local normalization or end-point fine-tuning (Figure 11). This is very important to demonstrate interchangeability of the measurements. The volume of bound fluid identified by NMR data determined the amount of irreducible bound water. The volume of water in the unflushed zone is significantly larger than BFV, indicating presence of free water. Volumetric saturation in the flushed zone derived from sigma identified only irreducible water and oil based mud filtrate. The combined information provided a comprehensive picture of reservoir behavior: mud filtrate is displacing all the movable water in the flushed zone. Sigma based interpretation is consistent with NMR, enabling the complementary use and reconstruction of the two methods.

Input Properties

Special Models

Additional Constraints

Figure 10: Petrophysical Analysis Parameter Initialization for LWD based logs interpretation


9

Figure 11: Multi-Mineral Evaluation using Logging While Drilling data

100 m


10

Figure 12: Petrophysical evaluation and textural analysis with LWD data

50 m


11

CONCLUSIONS The results shown in this paper demonstrate that when Wireline acquisition is either not possible or not economically viable, Logging While Drilling measurements provide equally effective data for a consistent petrophysical analysis under the proper drilling conditions. In the examples provided the LWD data proved to be reliable and demonstrated the potential to spare extra investigation costs, especially if the main evaluation in critical wells is executed with a complete set of LWD measurements. Drilling in carbonates inherently supports the LWD choice as the relatively low ROP in these formations helps to acquire better quality log data without requiring extra rig time. Workflows applicable to WL data can be replicated on LWD data with minimal changes. LWD measurements make formation evaluation in high angle/horizontal wells feasible where traditional WL services would not be practical. Finally, spectroscopy and NMR measurements are key tools to characterize complex carbonate reservoirs. Both of these measurements are available with LWD conveyance. NOMENCLATURE Rt True resistivity in unflushed zone

Rxo Flushed Zone Resistivity

WL Wireline data acquisition

LWD Logging While Drilling data acquisition

TCMR Total NMR Porosity

BFV Bound Fluid Volume (from NMR)

Quanti-ELAN* Multi-Mineral Petrophysical Analsysis

POR_QE Porosity Quality Control Output

Di Invasion diameter

Phie Effective porosity

Sw Water saturation in unflushed zone

Sxo Water saturation in flushed zone

* Mark of Schlumberger

ACKNOWLEDGMENTS The authors are grateful to OGX Petroleo & Gas and Schlumberger for granting permission to publish this work. Special thanks to Rubiel Ortiz, Schlumberger Reservoir Domain champion in Brazil who shared MDT data and relative interpretations, and to Vagner Costa, OGX Lead Reservoir Geologist, who provided constructive feedback during the preparation and the execution of the jobs. REFERENCES Archie, G.,E., AIME Transactions 31, 350-366, 1942 “The Electrical Resistivity Logs as an Aid in Determining Some Reservoirs Characteristics” Hansen P. and Shray F., 37th Annual Logging Symposium SPWLA, 1996. “Unraveling the Differences Between LWD and Wireline Measurements” Klein, J. D., Martin P.R, Allen, D.F. 36th SPWLA Annual Logging Symposium, 1995 “The Petrophysics of Electrically Anisotropic Reservoirs” Qiming Li, ChengBing Liu, Carlos Maeso, Peter Wu, Jan Smith, Hendrayadi Prabawa, John Bradfield. SPWLA 44th Annual Logging Symposium, 2003 “Automated Interpretation for LWD Propagation Resistivity Tools through Integrated Model Selection” M. Ribeiro, V. Costa, R. Guedes, P. Bittencourt, OGX; P. Ferraris, A. Guedes, Schlumberger. OTC-22738 2011. “Integrated Petrophysics and Geosteering Reservoir Characterization in the initial development phase of a carbonate reservoir – Campos Basin, Offshore Brazil.” Ferraris Paolo 2012 NT workshop BGRC Rio de Janeiro “Real Time Multi-Mineral Formation Evaluation with LWD Spectroscopy and NMR data” Raghu Ramamoorthy, Charles Flaum, Austin Boyd, Nikita Seleznev, Tom Neville SPWLA symposium 2008 Paper: B “A New Workflow for Petrophysical and Textural Evaluation of Carbonate Reservoirs” J.K. Hassall, Abu Dhabi Company for Onshore Oil Operations; Paolo Ferraris, M. Al-Raisi, Schlumberger; N.F. Hurley, Colorado School of Mines; A. Boyd, D.F. Allen , Schlumberger-Doll Research SPE 88683-MS ADIPEC 2004 “Comparison of Permeability Predictors from NMR, Formation


12

Image and Other Logs in a Carbonate Reservoir” Walid Najia, Mohammad Shaban, Hedhili Gossa, ZADCO, Abu Dhabi; Paolo Ferraris, Badarinadh Vissapragada, Mario Petricola, K.M.N. Namboodri, Schlumberger, Abu Dhabi, UAE SPE 78485-MS 2002 “Nuclear Magnetic Resonance (NMR), a valuable tool for Tar detection in a Carbonate Formation of Abu Dhabi” Asbjorn Gyllensten, Mohamed Ibrahim Al-Hammadi, Emhemed Abousrafa, ADCO; Austin Boyd, Raghu Ramamoorthy, Steve Neumann, Schlumberger; Thomas J. Neville, Schlumberger-Doll Research, SPE 2008 “A New Workflow for Comprehensive Petrophysical Characterization of Carbonate Reservoirs Drilled with Water-Base Muds” S. Al Arfi, ADCO, and D. Heliot, J. Li, X. Zhan, and D. Allen, Schlumberger ADIPEC 2006 “A New Porosity Partitioning-Based Methodology for Permeability and Texture Analysis in Abu Dhabi Carbonates” S. L. Herron , M. M. Herron Schlumberger-Doll Research SPWLA 37th Annual Logging Symposium, 16 – 19 June 1996, New Orleans, Louisiana, USA, Paper E. “Quantitative Lithology: an application for Open and Cased Hole Spectroscopy” E. Mirto, SPE, G. Weller, SPE, T. el-Halawani, SPE, J. Grau, SPE, M. Berheide, SPE, F. Allioli, SPE, and M. Evans, SPE, Schlumberger Oilfield Services; R. Berto, M. Borghi, and M. Firinu, Eni; and M. Giorgioni, Shell SPE Europec/EAGE Annual Conference and Exhibition, 12-15 June 2006, Vienna, Austria ISBN978-1-55563-230-4 “Developments in Sourceless Logging While Drilling Formation Evaluation: A Case Study from Southern Italy” V. Machado, P. Frederico Petrobras CENPES, P. Netto Petrobras, R. Bagueira Fluminense Federal University, A. Boyd, A. Souza Schlumberger Brazil Research and Geoengineering Center Rio de Janeiro, L. Zielinski Schlumberger-Doll Research Cambridge, MA , E.Junk Schlumberger , SPWLA 52th Annual Symposium 2011, Paper B “Carbonate Petrophysics in wells drilled with Oil-Base Mud” ABOUT THE AUTHORS Paolo Ferraris is a Principal Petrophysicist with Schlumberger Oilfield Services in Rio de Janeiro. He is currently D&M Petrophysics Domain Champion for IOCs in Brazil Geomarket. He graduated with honors at

Politecnico di Torino, Italy in 1981 with a MS degree in Electronics Engineering and since 1982 he has been working for Schlumberger holding several positions in field locations. He has been an SPWLA Distinguished Speaker for 2007-2008 season.

Irina Borovskaya is working in LWD Petrophysics Domain in Rio de Janeiro, Brazil. She received her PhD degree in Mathematical Modeling from Moscow Institute of Physics and Technology in 2007, and her BSc and MSc with honors in Applied Mathematics and Physics in 2002 and 2004, respectively. She started her career in Schlumberger-Doll Research Center in Ridgefield, CT as an intern in 2002. Irina joined Schlumberger in 2006 and worked on applications and modeling in geo-mechanics, reservoir engineering and petrophysics in the Moscow and the Boston Research Centers.

Mauro Ribeiro has been working at OGX Petroleo & Gas company since 2008 as Reservoir Geologist with focus in reservoir modeling, petrophysics analysis and horizontal well projects. He graduated with honors in Rio de Janeiro, Brazil, in 2002, and obtained MSc degree in Sedimentology/Stratigraphy in 2004. He worked at PETROBRAS S.A. between 2004 and 2008 as Reservoir Geologist and Petrophysist.

advances in formation evaluation independent of conveyance method

Documents