1. Depositional environment: the Anguille Marine field is a deep sea fan environment (i.e a turbidite) with a low sand/shale ratio. This geological description opens the discussion (unusual for previous simulation studies) and the geology features heavily in the flow properties and hence in the geological and reservoir models of this field.
2. Sequence stratigraphy: A more modern feature of reservoir simulation is that the
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Introduction and Case Studies
incorporate them into the 3D simulation model. These scales are also firmly linked to the geology (sedimentology) through the principles of sequence stratigraphy.
3. Geostatistics: Reference is made to how the geological features constrain the fine scale 3D models (of > 2 million blocks - which was large for the time) using geostatistical techniques. By the early 90s, the use of geostatistical methods was becoming more widespread and how it has been applied in this case is covered better by Refs. 1 - 5 in this paper.
Location and structure maps of Anguille Marine are given in Figures 1 - 4.
4. Brief field facts: Discovery 1962; primary depletion commenced in 1966 but reservoir pressure fell rapidly over the next 2 - 3 years and GOR increased; waterflooding from 1971 restored pressure support but channelling led to early water breakthrough; infill drilling not very successful due to lack of current understanding of complex reservoir geology; new approach in 1990 focused more strongly on the reservoir geology of this heterogeneous low sand/shale ratio system recognising the characteristic geometries of a tubditic fan - lobes channels, levees, slumps, laminated facies etc.
5. The approach: It is important in all reservoir simulation studies to have a clear logic to how we approach the simulation of a large complex reservoir system. Here they describe their general methodology although details are in Refs. 1 - 4 at the end of the paper. Basically they: describe and model upper reservoir/ extend to the whole reservoir/ try to translate the geological model to a practical simulation model. On the latter issue they describe the use of “partial models” where just a smaller sector of the reservoir is studied but lessons are taken back into the full model.
6. Reservoir description: Section 2 of the paper gives a sedimentological description of the reservoir as a “slope-apron fan” of complex lithology (depositional model Figure 3) in which 14 (simplified) facies were retained; criteria of composite log recognition of various facies shown in Figure 5. Some contradictory water breakthrough observations were noted. Table 1 gives sedimentary body dimensions (lengths and widths) for channels, lobes. levees/crevasse-splay, slumps, channels (Upper Anguille); Table 2 gives mean petrophysical characteristics. A very important final result for reservoir simulation is the identification of five scales of heterogeneity - Figures 6 and 7; this makes the geological analysis and information numerically useable.
7. Sedimentary history: In earlier reservoir simulation studies, and indeed up to the present time, it is rare to see sedimentary history discussed in terms of a sequence stratigraphic analysis (even mentioning the pioneering work on sea level changes of P. R. Vail et al, “Seismic stratigraphy and global changes of sea level”, in Seismic Stratigraphy, Applications to Hydrocarbon Exploration, AAPG Memoir 26, pp. 49-212, 1977). Chronostratigraphic correlations refer to the “timelines” of simultaneous deposition. This analysis underpins much of the reservoir description but we will not elaborate on it here.
8. Geostatistical modelling: Mainly discussed in Refs. 1 and 2 of this paper. Firstly, focus on geostatistical modelling of the 3D distributions of the major flow units (channels and lobes) and barriers (laminated facies or slumps) for the entire reservoir.
This is done as a “conditional” simulation where the distribution is constrained
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Introduction and Case Studies
(or conditioned) to the observed facies and reservoir quality observed at the wells. Secondly, the smaller scale heterogeneities are “unconditionally” simulated (synthetically) to yield average properties within the major flow units (see Ref. 2 in paper). The geostatistical simulation method used was “indicator simulation” (Refs.
1 and 8) which require the average frequency and variogram information.
9. Reservoir zonation: Six unit vertical reservoir zonation shown in Figure 10.
Simulations of lateral continuity within each of the units (five - not Middle Anguille, Figure 10) performed independently since they correspond to separate sedimentary phases. For horizontal zonation, Figure11 shows lateral zonation on LA2 and UA2 units showing directional trends and thus variograms with spatially variable anisotropy direction used in final model. Figures 12 - 15 show resulting correlation structures of the various units. Ends up with >2 million grid blocks in the full field 3D model.
10. Flow simulations: Discusses details of upscaling from fine grid stochastic model (>2 million blocks) to coarse grid simulation model (11,000 grid blocks). 11 vertical layers are retained to represent the reservoir layering with more blocks being used in the best reservoir units. Upscaling of absolute permeability at some “aggregation rate” (e.g. 4x4) is applied leading to areal block sizes of 200m x 200m - see Figure14.
Relative permeabilitiees were upscaled “on a typical block configuration” (details in Refs. 2 and 4). Additionally: Three major zero-transmissibility faults included in model; some WOC variation across field; depth varying bubble points assigned; 25 years of injection/production for history matching.
11. Simulation results: Initial pressure depletion results shown in Figure 16 - where 14 out of 17 wells show satisfactory pressure behaviour. Pressure behaviour and water breakthrough are poorly predicted during injection stage - Figure 17; water saturations around injectors shown in Figure18 - upscaling has “washed out” the finer scale strong anisotropy.
12. Model changes: Table 8 lists a number of sometimes quite radical changes to the model in order to achieve a better fit to observed field performance - Figure 15 shows differences in upscaled permeability maps. Continuing problems with injection predictions => - is geological model correct? - what is the real effect of upscaling?
13. Partial models: “Thin” model - Figure 19 shows the “thin” partial field model to verify reservoir geology; well AGM18 good water breakthrough match (Figure 20) - early breakthrough for well AGM29 (Figure 21). When thin model upscaled as in full field model (abs. k upscale + rel perm as before) - results in Figures 21 and 22 - breakthrough delayed in both wells but shape of BSW is satisfactory. Conclusions:
Thin model partly validates geological model; Some problems with upscaling not supressing breakthrough, making reservoir too connected and eliminating strong anisotropy. Test model - (50 x 20 x 56) model extracted from full field model. Figure 23 shows that an optimum upscaling aggregation rate (2 x 2 x 7) is found - they warn caution on this point. We note that if very reliable and general upscaling techniques were available, then this should be eliminated (more work has been done on this issue since 1992 - much of it at Heriot-Watt!).
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14. Conclusions:
• Sedimentology controls heterogeneity analysis when very wide variation in sandbody geometries is found (as in this case)
• Link understanding of reservoir history to sequene stratigraphy
• Litho-interpretation of seismic canʼt give paleo-direction when there is techtonic activity during sedimentation
• Multi-scale heterogeneity analysis essential to quantify sub-grid petrophysical properties
• Geostatistical indicator simulation is a good tool for modelling this multi- scale heterogeneity - trends can also be included
• Stochastic model for Anguille Marine constrained by geology gives hopeful first results
• If aggregation rate in upscaling is optimised, history matching is possible with the use of strictly controlled geological parameters
3.6 Case 3: Ubit Field Rejuvenation (SPE49165,1998)
Case 2: “ The Ubit Field Rejuvenation: A Case History of Reservoir Management of a Giant Oilfield Offshore Nigeria”, SPE49165, presented at the SPE Annual Technical Conference and Exhibition, New Orleans, LA, 27-30 September 1998, by C.A. Clayton et al (Mobil and Department of Petroleum Resources, Nigeria) See SPE 49165 paper in Appendix
Summary: This is another good example of where integrated reservoir management has greatly contributed to the success of a field redevelopment plan. In particular, a clearer understanding of the reservoir structural geology has been central to this process. The reinterpretation of the structural geology of the field (the fault blocks, compartments and slump blocks) was achieved using seismic data in a range of complementary ways. The Ubit reservoir is a prograding shallow marine system which has been tectonically disturbed. The downslope movements of the youngest sand sequences resulted in large scale slumping and block sliding although reservoir quality in these sediments is good to excellent. Important facts on the Ubit reservoir and this study are: STOIIP = 2.1 billion bbl oil; 37ºAPI black oil, Bo = 1.38, GOR 612 scf/stb, μo = 0.64 cp and μg = 0.16 cp; production from a relatively thin oil column (160 ft.) and a fairly thick gas cap (50 - 550 ft.). Previous average production = 30 MBD; after implementation of study recommendations (many horizontal wells etc.), expected production ≈ 140 MBD.
The notes on this SPE paper will not be very extensive and only a few of the main novel points will be discussed below.