This paper illustrates a novel approach (based on seismicfacies classification and 3D visualization) for tracking deltaicsand systems in the Urdaneta West producing field, LakeMaracaibo, Venezuela. As part of a major field review (vol-ume evaluation and well planning), the following oil-bearingreservoirs were studied:

• Oligocene sands (braided deltaic systems)• Eocene sands (lower deltaic systems)

Among the geologic challenges associated with develop-ing these reservoirs, the thinness of the sand layers and thelack of amplitude response of heavy oil-bearing sands werekey. Consequently, a dedicated geophysical workflow wasdesigned to address these issues. It comprises the followingsteps:

• Improving seismic resolution by applying high-frequencyimaging (HFI) processing (Figure 1)

• Implementing neural-network seismic facies classificationtechniques (loop-level trace-shape analysis for theOligocene reservoirs and volume classification for theEocene sands) to evaluate nonamplitude-supported plays

• Calibration of seismic reservoir indicators

This workflow integrated all available seismic attributes(including poststack attributes and impedance data), improvedthe seismic interpretation, and provided the means to predictsands (in a nonamplitude-supported play).

The geophysical results have been compared with the geo-logic data (cores and logs) and have confirmed the deposi-tional model established by the geologists.

Geologic challenges and technical solutions. The UrdanetaWest field is operated by Shell Venezuela on behalf of Petróleosde Venezuela SA(Pdvsa). Even though this field has been pro-ducing for nearly 40 years (with more than 100 well penetra-tions over the study area), exploitation and development ofOligocene/Eocene oil-bearing sands remain complex due tothe following geologic challenges:

• Thin sand layers (~10 ft on average) with limited lateralextent (fluvial and braided-delta deposits)

• Pore fluid characteristics (12-14° API oil with a low gas-oil ratio of 50 scf/bbl) resulting in a nonamplitude-sup-ported play. Amplitude/impedance variations are notindicative of hydrocarbon presence, but can be used aslithology indicators

• Poor continuity of seismic events within the Eocene reser-voirs resulting in complex seismic interpretation

• Density of faults (particularly in the Eocene reservoirs)affecting event correlation and possibly reservoir connec-tivity

To minimize these risks, Shell Venezuela conducted amajor field review performed by a multidisciplinary projectteam. The main objectives of this project were:

• To increase seismic resolution using HFI processing (res-

olution was enhanced from 100 to 30 ft, but individual sandlayers still could not be seismically characterized)

• To implement multiattribute seismic facies classification

SEPTEMBER 2004 THE LEADING EDGE 909

Tracking Tertiary delta sands (Urdaneta West, Lake Maracaibo,Venezuela): An integrated seismic facies classification workflowMANUEL POUPON, Shell International E&P Inc., Houston, Texas, U.S. JOSE GIL, DAVID VANNAXAY, and BICE CORTIULA, Shell Venezuela SA, Maracaibo

Figure 1. Comparison between original volume (top) and reprocessed HFIvolume (bottom) on SW-NE seismic line (reverse SEG convention; trough= increased acoustic impedance). Inset is structure map of Oligoceneunconformity with location of A-A’ section. Interpreted horizons from topto bottom: deep blue = maximum flooding surface, green = erosion-C, red= erosion-B, magenta = Oligocene unconformity, and yellow = Eoceneintrasequence. Note that the intra-Eocene fault (arrow) is clearly visibleon the HFI volume.

Figure 2. 3D view of the Oligocene unconformity with seismic trans-parency applied to low-impedance values. Note that the Eocene formationis characterized by chaotic events preventing any reliable horizon-basedanalysis (such as trace-shape classification).

techniques (trace-shape and multiattribute volume clas-sification) as an alternative to conventional amplitude-based analysis

• To apply volume interpretation techniques to speed up theinterpretation cycle (thereby freeing time for detailed pick-ing of reservoir sublayers)

• To integrate interpretation results through 3D visualiza-tion and ensure a consistent geologic model

Interpretation workflow. Due to the difference in seismicresponse within the reservoirs (continuous seismic withinOligocene formations versus chaotic events in Eocene, Figure2), two seismic classification techniques were considered:

• Interval-based classification for the Oligocene reservoirsusing neural network trace-shape analysis (Figure 4)

• Multiattribute volume classification (near- and far-stackanalysis) for the Eocene reservoirs (Figure 6)

The seismic attributes used for the classification includednear- and far-stack amplitudes, HFI amplitude, “thin bed”attribute, apparent polarity and P-impedance values.Principal component analysis (PCA) was used as a noisereduction technique prior to running classification. It alsohelped in addressing data redundancy inherent to multi-attribute analysis by selecting a relevant set of attributes forthe classification.

Comparison of seismic trace shape at wells with nor-malized net sand thickness (top of Figure 7) showed thatthe best sands produced a strong “fat” trough at the baseof the Oligocene interval. This observation was corrobo-rated by synthetic modeling (net-to-gross increase from 0.4to 0.8, bottom of Figure 7). Subsequently, key Oligocene andEocene wells were used to generate “supervised seismicfacies classes” and map the trace-shape signature of strati-graphic systems. These facies classes were then used to esti-mate sand distribution.

Seismic facies interpretation. The depositional model estab-lished by geologists based on log and core data for theOligocene formations was confirmed by classification results.In particular, the paleocoastlines observed on the regional seis-mic facies map (Figure 4) agreed with those obtained by welllog correlation. Locally, trace-shape classification providedunambiguous pictures of the sand channels, highlighting thepresence of an E-W braided delta, thus corroborating the firstobservations of a major E-W depositional system expressedby a high-impedance trend (Figure 3).

Additional seismic facies analysis, performed aroundspecific well clusters over intra-Oligocene sequences (~oneseismic loop), also helped in delineating channel systems ata smaller scale (Figure 5). These local seismic facies maps,combined with acoustic impedance analysis and sand dis-tribution maps (from wells), were the main source of infor-mation for new well proposals.

At the Eocene level, the multiattribute volume classifi-cation did not detect any evidence of a stratigraphic system.However, the use of volume interpretation techniques, suchas seismic transparency, revealed AVO anomalies in the pro-ducing interval. 3D visualization (Figure 6) showed directrelationships between AVO signature and Eocene structure,with cluster 1 anomaly solely on the crest of the structure.

The calibration of these qualitative observations (throughlog-based AVO modeling and seismic-to-well ties) was ham-pered by incomplete log suites and poor seismic data qual-ity. Overall, the AVO modeling results were inconclusive andshowed that Eocene reservoir AVO signatures are not wellunderstood at this stage.

Even though the seismic observations of an AVO sig-nature possibly associated to oil-filled sands could not beconfirmed by modeling, volume classification techniquescould be useful in further evaluating these complex Eocenereservoirs.

Seismic facies calibration: Empirical relationships versussynthetic models. The final (and critical) step in seismic-

910 THE LEADING EDGE SEPTEMBER 2004

Figure 3. Conventional interval analysis (lower Eocene). Top left: Isopach(X) versus average absolute amplitude (Y) crossplot showing tuningeffect. Bottom left: Average absolute amplitude interval map. Bottomright: Average impedance interval map. Note that the amplitude map ishighlighting NNE-SSW trends likely related to local tuning effects (Tsymbol on crossplot and map) due to formation thickening and onlaps.The impedance map revealed a SE-NW high-impedance trend (arrow) andlow-impedance lobe (see black outline on map and A-A’ section) related tomain flow direction of the delta system.

Figure 4. Unsupervised multiattribute trace-shape classification map (15classes) over Oligocene reservoirs and model traces (amplitude HFI,apparent polarity, P-impedance and thin bed). Paleocoastlines interpretedfrom well correlation match those interpreted on seismic facies maps. Theclassification map highlights a delta system characterized by multiplechannels branching out from an eastern source (zoom view).

based quantitative interpretation is calibration. In the caseof the Oligocene reservoirs, two approaches were consid-ered to calibrate seismic facies classes:

• Petro-acoustic modeling based on a key well requires atleast one well with complete logsuites—Vp, Vs, Rhob, GR, Poro, Sw(i.e., a recent well)

• Statistical/empirical analysis ofseismic trace shapes at wells (~40control points). This approachrequires several wells with at leasta GR curve (i.e., “old” wells are suit-able)

Both techniques confirmed thattrace shape could be used as a sandindicator within the Oligocene reser-voirs providing the seismic signature isnot affected by imaging artifacts. Forinstance, wells in the vicinity of a faultare obviously not appropriate to super-

SEPTEMBER 2004 THE LEADING EDGE 911

Figure 5. Seismic facies analysis over a 20-ms intra-Oligocene sequence.Comparison with average amplitude and impedance map over the sameinterval. Note that the seismic facies map improves the definition of theESE-WNW channel characterized by a “fat” trough development (as wellas high amplitude and impedance values).

Figure 6. SW-NE section through unsupervised AVO volume classifica-tion (eight classes) over the Eocene interval with corresponding clustersdisplayed on a near-far AVO crossplot (bottom left). Note that AVOcluster 1 (in red) is exclusively over Eocene structural highs (arrow).

Figure 7. Seismic facies calibration. Top: Trace-shape signature at keywells. Wells in green correspond to oil-filled Oligocene sands; wells inblue correspond to wet Oligocene sands. Wells are sorted in decreasingnormalized sand thickness indicators. Note that thicker sand packages areexpressed by a large trough at the base of the interval (red square).Bottom: Synthetics based on a key Oligocene well. Note that a net-to-gross increase from 0.4 to 0.8 results in a trough development at the baseof the Oligocene (arrow) similar to the one observed on seismic traceshapes at key wells.

vise neural network pattern recognition, since their seismictrace shape is not representative of the signatures of reser-voir sands.

The empirical/statistical analysis of HFI trace-shape sig-nature at key Oligocene wells confirmed the presence of alarge trough developed at the base of the interval within thethicker sand package (top of Figure 7). These observationshave been validated by synthetic models based on theOligocene key well, where an increase of net-to-gross from0.4 to 0.8 resulted in a development of a wide trough at thebase of the reservoir interval (bottom of Figure 7).

Practices worth replicating. Seismic facies classificationtechniques could be implemented in any field review as partof seismic interpretation workflows, complementing theconventional structural and amplitude-based analyses.However, trace-shape classification should only be consid-ered when loop-analysis is applicable (i.e., the presence ofa continuous seismic event is required).

In the case of poor seismic imaging, heavily faulted areasand/or lack of a regional continuous marker (e.g., a maxi-mum flooding surface), multiattribute volume classifica-tion should be used as an alternative to horizon-basedclassification. Some limitations of these volume classifica-tion techniques are:

• Volume techniques use sample-by-sample classification,while trace-shape analysis uses higher resolution (sub-sample analysis) over rocks of roughly similar age, whichis more suitable for detailed reservoir analysis

• Volume classification is sensitive to the number and typeof input attributes

• Data QC is required to address any mis-alignments between pre- and poststackattributes prior to running classification

In Eocene reservoirs, these issues wereaddressed by:

• The use of HFI-reprocessed seismic (withderived poststack attributes)

• PCA and seismic modeling to select arelevant attribute suite for volume clas-sification

• QC of near- and far-stack alignment overtargeted reservoir areas

In the case of the Oligocene reservoirs,the specific interval chosen for analysis wascritical to properly assess thin-sand reser-voirs. A seismic facies analysis performedover a single loop interval and over a lim-ited area (i.e., around a proposed well loca-tion, Figure 5) proved to be more informativefor well development planning than regionalseismic facies maps defined over a largedepositional sequence (Figure 4).

Conclusions. Seismic trace shape and vol-ume classification techniques are graduallyintroduced into the seismic interpretationworkflows as new ways to look at seismicdata and complement the conventional struc-tural and amplitude analysis (Coléou et al.,

2003). These techniques have proven successful in stratigraphicplays such as Tertiary fluvial deposits of Western Venezuela(Linari et al., 2003), where amplitude alone fails to character-ize reservoir properties.

This workflow has contributed to the development of asand prediction tool (in a nonamplitude-supported play) andconfirmed the deposition model established by geologistsfrom core and log observations (Figure 8). Proper acousticmodeling and well-to-seismic calibration remains the criti-cal step to turn “qualitative seismic facies classes” into“quantified reservoir properties” used as input for reservoirmodeling.

Suggested reading. “Unsupervised seismic facies classification:a comparison of techniques illustrated by case studies” by Coléouet al. (TLE, 2003). “An evaluation of HFI test results” by Gil andEngel (Shell Integrated Subsurface Conference, 2002). “Seismicfacies analysis based on 3D multiattribute volume classification:La Palma Field (Maracaibo, Venezuela)” by Linari et al. (TLE, 2003).TLE

Acknowledgments: The authors thank Pdvsa and Shell Venezuela SA forpermission to present this work, and the Urdaneta-West team in Maracaibo(SVSA) and Bellaire (EPT-W)—in particular Charlotte Martin, MariaBalzarini, and Fa Dwan—for sharing their expertise. Special thanks toMichael Cooper and Peter Diebold (Shell International E & P) for review-ing this paper. HFI processing is a service of Geotrace. Stratimagic andSeisFacies are trademarks of Paradigm Geophysical.

Corresponding author: manuel.poupon@shell.com

912 THE LEADING EDGE SEPTEMBER 2004

Figure 8. Comparison between modern delta sands - Knife River delta, Canada (left - E-Wmirror view of Landsat image, courtesy of USGS) and Oligocene sand system observed onseismic facies map (inset). Core analysis over the Oligocene formations has confirmed thepresence of fluvial deposits developing in time into fluvial-dominated deltas. This depositionalmodel is in agreement with seismic facies interpretation. Three distinct environments havebeen identified by sedimentologists on core data: (1) upper delta plains with exposed overbanksplays and floodplain mudstones, (2) lower delta plains and (3) delta front facies with highlybioturbated facies and the presence of planolites, rizocorallium, thallassinoides, ophiomorpha,skolithos, paleophycus, teichichnus suggesting brackish waters.