Reservoir characterization is the key to a successful oil field development program. The recovery efficiency of any reservoir is influenced by its heterogeneities; particularly the distribution of porosity and permeability. To develop a reservoir model that represents the reservoir properties we must be able to define the vertical distribution of reservoir properties “flow units” and each flow unit has its own characteristics which control fluid flow behaviour. The understanding of flow units allows us to identify preferential flow zones. This study involves the determination of the number and distribution of hydraulic units (flow units), key flow unit characteristics and qualitative interpretation of flow performance using Stratigraphic Modified Lorenz Plot (SMLP) and Flow Unit Speed (FUS) parameter in the three selected wells of “Aqua Field”, Niger-Delta, Nigeria. A total of forty-two (42) flow units were identified throughout the hydrocarbon bearing intervals of Wells B, D and E. Well B has sixteen (16) flow units with six (6) speed zones and ten (10) baffles zones. Well D has five (5) flow units delineated, with three (3) speed zones. Also a total of twenty-one (21) flow units were delineated for Well E with nine (9) flow unit speed zones; the rest being baffles. The number of flow units delineated is an indication of the extent of the reservoir heterogeneity. The dominance of the speed zones to the baffles zones in a hydrocarbon bearing interval is an important factor in the flow performance and recovery efficiency during enhanced oil recovery. These various hydrocarbon bearing intervals of “Aqua Field” are dominated by baffles and an anticipated long term production will be sustained by the baffles zones. This will be characterized by a steady to slow decline production behaviour. This study has shown that Stratigraphic Modified Lorenz Plot (SMLP) is a cost effective, quick look method of characterizing petrophysical flow units.



1.1 Background Discussion

Petroleum geologists have long recognized the need of defining quasi-geological engineering units to shape the description of reservoir zone as storage containers and reservoir conduits for fluid flow. The exploitation plan for petroleum reservoirs is based on results from production forecasts, which are obtained from detailed reservoir studies. It is important to know how much oil, gas and water exist in place and how the fluids will move through the reservoir. In particular, fluid movement is difficult in highly heterogeneous reservoirs and considerable efforts to develop a good reservoir description that adequately defines the vertical and lateral distributions of reservoir properties are needed. Primarily the porosity and permeability distributions are considered. This is better understood when reservoir heterogeneity is better defined which has profound effect on all phases of hydrocarbon recovery. The variation of reservoir properties gives rise to different hydraulic (flow) units within a lithologic formation. A flow unit is a volume of total reservoir rock within which geological and petrophysical properties that affect fluid are internally consistent and predictably different from other properties of other rock volumes (Ebanks, 1987). A given flow unit exhibits similar permeability-porosity relationship and has similar properties for fluid flow. Flow units of a reservoir are relatively easy to determine using three parameters, porosity, permeability and bed thickness to generate cumulative flow capacity and storage capacity for crossplot (Gunter et al.,1997).The vertical variation in flow and storage capacity characterized by unique slope line give rise to different flow units which are indications of key flow unit characteristics such as conduits, baffles or barrier (Rushing and Newsham,2001).The flow unit division allows fluid flow within the reservoir to be better understood and categorized in a useful manner for simulation analysis and reservoir management.

1.2 Research Aims/Objectives

The Niger-Delta Basin has numerous marginal productive or abandoned oil fields. Typically production records are non-existent which hampers further development interest. The purpose of this study is to use a quick look method of characterization when data are limited. The permeability-porosity relationship within each flow unit allows us to identify and characterize the flow units using the Gunter et al. (1997) flow unit characterization method. However, without permeability distribution, flow unit prediction is not possible. This research seeks to predict flow units using only well log data when no core data and seismic data are available for analysis. The use of the core and seismic data will aid in refinement and validation of estimated porosity-permeability values obtained from well log and also the identification of fractures, faults and other structures which contributes or limits to the fluid flow potential of a reservoir.

By following the methodology the research aims to

  • identify the number of flow units within a reservoir using well log data;
  • predict the key flow unit characteristics in each hydrocarbon bearing zone;
  • determine the distribution of flow units within the hydrocarbon bearing zones; and
  • make a qualitative flow performance interpretation using the slope of inflexion and flow unit speed parameters.

1.3 Study Area/Tools

The Aqua-field is a mature field situated in the Central Swamp I Depo-Belt of the Niger Delta area (Fig.1a & c). Three wells, namely Well – B, Well – D and Well – E, used for this study were drilled to total depths of 11930 ft, 11600ft and 13132ft respectively (Fig.1b). The dataset used for this research is  three conventional open hole well logging data which have Gamma Ray(GR),Caliper (CAL-X),Sonic transit time (ΔT),Bulk density (ρb) and Resistivity (R-ILD,R-ILS and R-MSFL), made available by Shell Petroleum Development Company (SPDC) of Nigeria.

1.4 Literature Review

Lorenz coefficient provides a convenient method for observing flow capacity as a function of storage capacity; however the method does not provide a spatial representation of either the flow or the storage capacity. The proper selection of flow zones within a particular reservoir has been a subject of interest in both formation evaluation and reservoir modeling (Testerman, 1962; Nelson, 1994). Hearn et al. (1984) introduced the concept of flow unit to determine the distribution of rock types that most strongly control fluid flow and defined a flow unit as a reservoir zone that is continuous both laterally and vertically and has similar permeability, porosity and bedding characteristics. In their study, stratigraphic sequence provided the initial framework for flow unit delineation with petrophysical properties and petrographic analysis.

Ebanks (1987) defined the fundamental concepts of flow units as a volume of the total reservoir rock within which geological and petrophysical properties affecting fluid flow are internally consistent and (predictably) different from properties of other rock volumes or flow units. Flow units subdivide the reservoir volume into geo-bodies (layers) appropriate for flow-simulation studies. Amaefule et al. (1993) correlated Flow Zone Indicator (FZI) with a combination of wireline-log curves to identify flow units at uncored wells. They also found that the permeability –porosity relationship in the Niger- Delta is non-linear and its variability appears to be both texturally and mineralogical controlled. For flow unit definition in uncored wells, Holtz and Hamilton (1996) proposed that flow units have interdependent petrophysical parameters and log signatures correlative over distance. Various methods have been used to characterize flow units at uncored wells such as rank correlations on wireline logs (Abbaszadeh et al., 1996); saturation and depth profiles (Martin et al., 1997); stochastic modeling of shale fraction (Vsh) and effective porosity (Moon et al., 1998); algorithms predicting rock types from wireline logs (Davies and Vessell, 1996; Davies et al., 1999). Gunter et al. (1997) method uses only the three easily obtained parameters; porosity, permeability, and thickness to calculate flow units in terms of their capacity to store and transmit fluids within the reservoir. Flow units have been defined using Lorenz plots, a petrophysically based graphical tool and have been reported by Gunter et al., (1997a, b). Alper (2000), Maglio-Johnson (2000), Ali-Nandalal and Gunter (2003), and Balossino et al. (2006) used different methods to estimate permeability at uncored wells to identify flow units with Stratigraphic Modified Lorenz plots (SMLP). The development and application of the hydraulic flow unit model is stimulated by the common problem of permeability prediction in uncored but logged well (Svirsky et al., 2004). Lawal and Onyekonwu (2005) defined flow unit delineators for sandstones and carbonates by geometrically averaging all characterizing parameters from five existing models.

1.5 Methodology

The challenge of understanding and predicting reservoir properties is two folds; first to describe reservoir geologic heterogeneities realistically and quantitatively and second to predict reservoir flow behavior in the presence of all heterogeneities accurately and efficiently. In order to achieve the above mentioned challenge this study was approached using petrophysical derived parameters (porosity and permeability) from well log analysis for three wells in Aqua-Field to generate effective porosity and permeability values on a 0.5 feet (0.15m) interval. The generated values were used to calculate cumulative flow capacity and storage capacity parameters for Stratigraphic Modified Lorenz (SML) and Flow Unit Speed (FUS) plots within the hydrocarbon bearing intervals as diagrammatically shown in Figure 2. The well log data were first loaded into the Petrel software for log response plots. Further calculation and generation of plots were made using the Excel spreadsheet software. The approach used in accomplishing this task is as follows: –      

  • The discrimination of potential reservoir rock from non-permeable rock was done using the Gamma Ray log because it records the abundance of the radioactive isotopes of Thorium, Uranium and Potassium. They are usually concentrated in shale and less concentrated in sandstone.
  • The resistivity log helped in the detection of hydrocarbon bearing zones by high resistivity values and also an anti-correlation between the density and resistivity log for hydrocarbon zone and low resistivity for water zones. Also tight zones which could give high resistivity were also considered.
  • A complete quantitative evaluation using log response values to determine volume of shale (Vsh), effective porosity (φe), water saturation (Sw), hydrocarbon saturation (Sh), irreducible water saturation (Sirr) and permeability (k) for the hydrocarbon bearing zones using empirical and theoretical relationships of well log analysis.
  • Tabulation of φ-ft (product of porosity and thickness) and k-ft (product of permeability and thickness) for each of the 0.5 feet (0.15m) interval were used and expressed as percentage  of the total φ-ft and K-ft summed over the entire hydrocarbon bearing zone.
  • Cumulative φ-ft (%) and cumulative K-ft (%) were calculated for every 0.5 feet (0.15m) of the hydrocarbon bearing interval.
  • A graphical plot of the Stratigraphic  Modified Lorenz Plot (cumulative flow capacity against storage capacity) was plotted for each hydrocarbon bearing zones in a Cartesian plane and flow units were delineated based on changes in slopes inflections.
  • A plot of Flow Unit Speed (FUS) was generated by plotting the ratio of cumulative k-ft% and cumulative φ-ft% against depth to confirm the key flow characteristics already delineated using the Stratigraphic modified Lorenz plot.