International Journal of Geophysics

International Journal of Geophysics / 2019 / Article

Research Article | Open Access

Volume 2019 |Article ID 1706416 |

U. C. Omoja, T. N. Obiekezie, "Application of 3D Seismic Attribute Analyses for Hydrocarbon Prospectivity in Uzot-Field, Onshore Niger Delta Basin, Nigeria", International Journal of Geophysics, vol. 2019, Article ID 1706416, 11 pages, 2019.

Application of 3D Seismic Attribute Analyses for Hydrocarbon Prospectivity in Uzot-Field, Onshore Niger Delta Basin, Nigeria

Academic Editor: Marco Bonini
Received11 May 2018
Revised30 Oct 2018
Accepted26 Nov 2018
Published14 Jan 2019


3D seismic interpretative study was carried out across the Uzot-field in the western Coastal Swamp Depobelt of the onshore Niger Delta Basin, Nigeria, with the aim to identify possible hydrocarbon leads and prospects away from the drilled zone, utilizing seismic amplitude attributes. The method employed in this study involved systematic picking of faults and mapping of horizons/reservoir tops across seismic volume and extraction of seismic attributes. Structural analysis indicates the presence of down-to-basin footwall and hanging wall faults associated with rollover anticlines and horst-block (back-to-back fault). Generated time and depth structural maps from three reservoir intervals (D3100, D5000, and D9000) revealed the presence of fault dependent closure across the field. Analyses of relevant seismic attributes such as root-mean-square (RMS) amplitude, maximum amplitude, average energy amplitude, average magnitude amplitude, maximum magnitude attribute, and standard deviation amplitude, which were applied on reservoir tops, revealed sections with bright spot anomalies. These amplitude anomalies served as direct hydrocarbon indicators (DHIs), unravelling the presence and possible hydrocarbon prospective zones. In addition, structural top maps show that booming amplitude is seen within the vicinity of fault closures, an indication that these hydrocarbon prospects are structurally controlled. Results from this study have shown that, away from currently producing zone at the central part of the field, additional leads and prospects exist, which could be further evaluated for hydrocarbon production.

1. Introduction

Oil and gas in the Niger Delta Basin are principally produced from accumulations in the pore spaces of reservoir rocks from sandstones and unconsolidated sands predominantly in the Agbada formation [1]. The goal of hydrocarbon exploration is to identify and delineate structural and stratigraphic features associated with hydrocarbon generation, deposition, migration, and entrapment. These structural and stratigraphic traps could be very subtle and are, therefore, difficult to map accurately. However, the advancement in 3D seismic reflection methodology and borehole geophysics has made it possible to map such structural and stratigraphic configuration with high degree of reliability and precision thus reducing the risk factor associated with hydrocarbon exploration [25]. Seismic attributes analysis being an integral part of 3D seismic reflection interpretation is one of these advancements [69]. Seismic attributes have been widely used for detection of hydrocarbon reservoirs [913]. This study is aimed at imaging the subsurface structure of Uzot field with a view to delineate hydrocarbon prospect using seismic amplitude attributes as direct hydrocarbon indicators (DHIs).

The field Uzot is an onshore field located in the western part of the Niger Delta Basin (Figure 1(a)). The Niger Delta Basin is situated at the North Eastern margin of the Gulf of Guinea on the West coast of Africa and it covers an area of about 75,000km2 and is at least 11km deep in its deepest parts [14, 15]. The Niger Delta province consists of three litho stratigraphic units all of which are strongly diachronous. [1, 16, 17] These units from the oldest to the youngest include the Akata Formation which is made up of dark gray shales and silts with rare streaks of sand of probable turbidite flow origin and is estimated to be 7000m thick in the central part of this clastic wedge [1]. This formation is composed of marine shales form the main source rocks for petroleum. The Agbada Formation which occurs throughout the Niger Delta clastic wedge and has a maximum thickness of more than 3,000m [1]. This formation is the hydrocarbon-prospective sequence in the Niger delta, where the sand serves as reservoirs and shale as the source rock [1]. The Benin Formation which comprises the top part of the Niger Delta clastic wedge, from the Benin-Onitsha area in the north to beyond the present coastline [16].These three major lithostratigraphic units defined in the subsurface of Niger Delta reflect a gross upward-coarsening clastic wedge [18]. The sedimentary wedge in Niger Delta has been laid down in five depobelts with the oldest lying furthest inland and the youngest located offshore [19]. These depobelts includes: Northern Delta, Greater Ughelli, Central Swamp, Coastal Swamp, and Offshore depobelts. Each depobelt is a separate unit that corresponds to a break in regional dip of the delta and is bounded landward by growth faults and seaward by large counter-regional faults or growth fault of the next seaward depobelt [1, 20]. The Uzot field, which is the study area, lies at the western part of the Coastal Swamp Depobelt (Figure 1(a)). The Coastal Swamp Depobelt is characterized by structural complexity due to internal tectonics on the modern continental slope, associated with growth faults, rollover anticlines, collapsed crests, and back-to-back features [5, 20, 21].

2. Methodology

The data set used for this study includes suites well log from five wells (concentrated mainly at the central) and 3D seismic data (Figure 1(b)). The seismic volume comprises 680 inlines and 511 cross-lines. The well log suites made available are gamma ray log, resistivity log, density log, neutron log, well-tops, and check-shot data. Check-shot data provided the velocity information needed to associate formations encountered in the wells with reflections on the seismic sections. Well to seismic tie was done by linking check-shot data to wells and displaying on seismic section. Good relationship between well log data and seismic data was used for identifying key intervals of interest, that is, reflections for horizon picking using well-tops and gamma ray log as a guide. Lithologies and reservoir packages were delineated using the gamma ray log. Resistivity log was integrated with neutron and density logs to delineate hydrocarbon zone and discriminate fluid types, respectively. Three reservoir intervals were correlated across the five wells using the available well-top data. Faults were identified and picked, systematically on the seismic sections. Three surfaces/horizons (reservoir tops) were determined using the reflection characteristics of the 3D seismic volume, stratigraphic indicators, and the nature of the gamma ray curves that characterize this area. Petrel™ software was used for well correlation and seismic interpretation. Polynomial plot was generated using time and depth values from check-shot data (Figure 2). This generated plot was used in depth converting time structure maps that were produced. In order to ascertain whether the mapped horizons were hydrocarbon bearing, seismic amplitude attributes analyses were carried out. Brown Classification [23] was adopted in the application of several seismic attributes such as the Root Mean Square amplitude (RMS), Maximum Amplitude, Average Energy, Average Magnitude, Maximum Magnitude, and Standard deviation of amplitude. Hydrocarbon prospects were identified using RMS amplitude attribute.

3. Results and Discussion

3.1. Well Log Reservoir Correlation

Selected reservoir tops were correlated across wells. Figure 3 depicts the correlation of reservoir interval D3100 package across wells; this reveals that sediment packages thicken from North to South (basinwards). This thickening is probably due to the influence of faulting (sediment thickens at downthrown section) on stratigraphy associated with syndepositional deformation within the Niger Delta Basin [24].

3.2. Seismic Interpretation

Fault structures were observed on seismic section (Figures 4(a) and 4(b)). Uzot field is marked by three major normal growth faults that extends across the field and several synthetic and antithetic normal growth faults (Figures 4 and 5). Reservoir tops D3100, D5000, and D9000 also show thickening of sediment pattern (Figures 4(b) and 4(d)). These mapped intervals were characterized by high amplitude with moderate-to-good continuity reflections, mostly disrupted by some truncations, which are more of fault related.

The result of fault interpretation shows that Uzot Field is characterized by multiple growth faults, footwall, hanging wall, rollovers anticlines, antithetic or counter fault, and horst block structures. This is typical of the Niger Delta Basin faulting system [1, 5, 25]. Drilled wells used in this work were within extensive fault blocks, which shows that these major faults act as trap for hydrocarbon accumulation (Figures 4, 5, and 6).

Generated time and depth structural maps of the mapped reservoirs showed that structural highs exist in the northern and central parts of the field while the southern part of the field is characterized by structural lows (Figure 6). These time and depth structural maps of these horizons indicate the presence of rollover anticlinal structure at the central part of the field. Two of the three major faults bound this anticlinal structure (Figure 6). All the wells drilled in this study targeted this anticlinal structure. This means that the trapping mechanism of the field is largely by means of this rollover anticlinal structure and fault closures.

3.3. Seismic Attributes Interpretation

Seismic attributes analyses carried out on extracted amplitude map for each of the three reservoir tops (D3100, D5000, and D9000) showed that strong amplitude anomalies exist at the central part of the field and parts of northeast, northwest, and southwest sections (Figures 7(a)7(f), 8(a)8(f), and 9(a)9(f)). The central part of the field where these strong amplitude anomalies were observed corresponds to the observed rollover anticlinal structure in the field. Other parts of the field where the amplitude anomalies were observed also correspond to the identified structural closures found in the field.

Results indicate that strong amplitude anomalies are structurally controlled as they are seen occurring near fault on structural top maps. The seismic amplitude attributes analyses showed that bright spot anomalies are indicative of hydrocarbon presence [23, 26]. All the six amplitude attributes maps generated for reservoir tops of interest were seen to have similar pattern of bright spot anomaly, which are likely associated with of facies and/or fluid content [26]. In addition, these anomalies are seen on structural high, which suggested prospect conformity with regional structural high (Figures 7(a)7(f), 8(a)8(f), and 9(a)9(f)).

3.4. Hydrocarbon Prospect Identification

Evaluation of hydrocarbon prospectivity reveals that the study area has high fault density (down-to-basin faults), which makes trapping structures available for hydrocarbon accumulation, thus providing possible hydrocarbon leads. Within the three reservoir intervals, the central part denoted with “X” has been previously evaluated and seen to have potential trap that turned into an oil/gas field when drilled, hence a good hydrocarbon prospect. This prospect is quite evidenced from structural top and depth maps and several amplitude maps that were generated. Prospect “X” shows booming amplitude that is structurally controlled, which has given rise to several drilling campaigns within the zone (Figures 10 and 11). However, away from the “X” prospect this study has been able to identify other prospective zone characterized by good amplitude response and trapping structures.

The root-mean-square amplitude attribute was used for the identification of prospective zones because it is more sensitive to direct hydrocarbon indicators (DHIs) than others and its pattern of bright spot anomaly superposition on the structural closures are discrete (Figures 10(b), 11(a), and 11(b)). Five hydrocarbon prospective zones each were identified for D3100 and D5000 whereas six were observed in D900 reservoir intervals (Figures 10, 11(a), and 11(b)).

Four out of five identified prospective zones (A, C, D, and E) in D3100 reservoir top show two-way fault dependent closures (since they are bounded by two faults) while zone B shows a three-way closure bounded by one faults. All these prospective have been classified a hydrocarbon leads, since there are good trapping structures and hydrocarbon presence. However, zones A and D rank the best hydrocarbon lead within this reservoir, considering the well-developed entrapment mechanisms for hydrocarbon accumulation.

For the D5000 reservoir top, zones A and C show three-way fault dependent closures with moderate amplitude response whereas zones B, D, and E reveal a two-way fault dependent closures with high amplitude response. Considering its structural style and moderate to high amplitude response, zone D for D5000 reservoir offers the best hydrocarbon lead when compared with other zones.

Analyses reveal that, out of the seven zones, identified as hydrocarbon leads in D9000 reservoir, E and F show two-way fault dependent closures whereas A, B, C, and D depict three-way fault dependent closures. The structural style of zone E for D9000 reservoir top is similar to that of prospect D in D5000 with moderate to high amplitude response. The presence of key structural styles such as rollover, faulted anticlinal dip closures, upthrown fault or footwall closures, and downthrown fault or hanging-wall closures is typical producing field in the Niger Delta Basin and that of most giant fields [1, 24]. This study has shown that, away from the producing zone (prospect “X,” which is common to all the three reservoir tops and characterized by rollover anticlinal structure at the central part of the field), the application of seismic attribute analysis has unravelled several hydrocarbon prospective that could be further revalidated and evaluated to a hydrocarbon prospect.

4. Conclusion

The result from the application of 3D seismic amplitude attribute analyses in Uzot-Field, western Coastal Swamp Depobelt of the onshore Niger Delta Basin, indicates that away from the producing zone at the central part that their exit other hydrocarbon prospective zones. Several prospective hydrocarbon leads identified within three studied reservoir (D3100, D5000, and D9000) intervals show good trapping structures such as rollover anticlines, footwalls, and hanging walls, which support hydrocarbon accumulation. The time and depth structural top maps of the reservoirs indicate that the identified prospective zones are characterized by fault dependent closures. Extracted amplitude maps revealed that zones with good amplitude response, which indicates the presence hydrocarbon bearing reservoir section, were seen occurring around faulted zones. This implies that the prospective zones are structurally controlled. In addition, root-mean-square amplitude attribute gave a reliable insight into prospecting for reservoir structures and deposits in the subsurface across the Uzot field. Overall, study has demonstrated that the application of seismic amplitude attribute, which offers insight on hydrocarbon presence and distribution of reservoir sand, could help unravelled prospective intervals where there are no well controls.

Data Availability

The data used to support the findings of this study are available from the corresponding author upon request.

Conflicts of Interest

The authors declare that they have no conflicts of interest.


The authors are grateful to Department of Petroleum Resources (DPR) and Port-Harcourt office for granting the permission to obtain the data used for this research work. They thank the Shell Petroleum Development Companies in Nigeria (SPDCN) for provision of the data that was used for this research work. They are also grateful to Schlumberger and ExxonMobil for the provision of the Petrel Software and Workstations, respectively, and also to Chidozie Izuchukwu Princeton Dim and Chukwudike Gabriel Okeugo for their technical contribution to this paper.


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Copyright © 2019 U. C. Omoja and T. N. Obiekezie. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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