fax 01-972-952-9435. AbstractGeoscientists and reservoir engineers are very well acquainted with the terms "net-to-gross (NTG)" and "petrophysical cut-offs" or just "cut-offs". The significance of these terms is ultimately to define productive zones in the reservoir for hydrocarbon exploitation. However, there has been marked misunderstanding surrounding the usage of the term, net-to-gross and implicitly, the derivation of cut-offs which are limiting values used in expressing the netto-gross ratio. While the geologist may be concerned with the pay for evaluating hydrocarbon-in-place and the ultimately the estimation of economically producible reserves, the simulation engineer is more concerned with fluid flow for pressure support in the reservoir 1 . The significance of this paper is to consider the different cut-offs selection methods, the varying interpretation of net-to-gross ratios and the implications inherent in such methods. A case study from a field in the NigerDelta is also carried out to reveal the impact of such selection criteria especially in rocks with congenital weak hydraulic properties which cannot be excluded at geologic correlation stage 2 . The effect of cut-off parameters on oilinitially-in-place (OIIP) calculation was also investigated and a sensitivity analysis carried out on the petrophysical parameters to reveal the impact of the dynamically conditioned cut-offs selection on the petrofacies. Multiple Monte Carlo realizations were also employed to obtain probabilistic OIIP estimates rather than a single deterministic result.

Weak hydraulic units occur frequently in many Niger Delta fields. This makes the characterization of reservoirs in such fields quite challenging. In this work the interpretation procedure, adopted model and algorithm were chosen such that each unit is treated separately to make the evaluation process as detailed as possible. Also, a conscious effort was made to incorporate functions in our adopted model that take care of the factors responsible for the weak hydraulic units in the reservoir. The application of cut-offs was done in a manner that blocked properties and predictive algorithm only relate to intervals that will contribute to production. This approach is necessary to improve the precision and predictive algorithm of porosity, permeability and water saturation that form part of the reservoir evaluation process. Usually the inclusion of units with weak hydraulic properties in the evaluation of hydraulic storage at the onset will decrease and weaken the precision of the evaluation process if cut-off were not applied. Also, the approach resulted to a construction of the simplest dynamic model that is compatible with the static model which is the objective of every reservoir characterization. The prime aim of this approach is a more precise reservoir characterization as against a mere approximate. Introduction Most reservoirs formed within a progradational to retrogradational parasequence have rock units that are of weak hydraulic properties which are typified in many Niger Delta fields. The description of such reservoir needs to be precise to reduce the amount of hydrocarbon left behind pipe. It is therefore expedient to develop appropriate methodology and algorithm in the description of such reservoirs. Hydraulic units have previously been defined as the representative elementary volume of total reservoir rock within which geological and petrophysical properties that affect fluid flow are internally consistent and predictably different from properties of other rock volumes1. When such units are of small transmissibility they are said to be weak. Geologically the weak hydraulic units form part of the reservoir succession (congenital), but they do not contribute significantly to the evaluation of the hydrocarbon in place or the estimation of reserves2. This is due to the poor storage capability of these units. The permeability values of these units are also very low; hence the transmissibility is also invariably small compared to the other successions in the reservoir rock.

Reservoir flow zones reflects group of rocks that have similar geologic, physical properties and depositional environment that affect fluid flow. Variations in rock properties result from depositional, diagenetic and post-depositional changes. Aside from a geologic approach, statistical analyses are required to verify the existence of these flow zones. A statistical zonation technique developed by Testerman1 to identify and describe naturally occurring zones in a reservoir and to correlate these zones from well to well was used here. The flow performance is a strong function of the average permeability, and therefore of the statistical flow unit definition method used. Five reservoir flow zones were established based on the geologic litho-stratigraphic correlation using gamma ray and resistivity logs. This is against the two flow zones estimated from statistical correlation. Where this happens, the simulator may lump together several geologic layers. Lumping involve adding layers that have similar physical properties. The number of zones depends on the computing limitation and any other constraints of the simulator. Reconciling these two differences provides a better input into numerical flow simulation. Introduction Accurate well correlations are paramount for a reliable reservoir characterisation. All geologic modelling have their foundation in correlation work. Therefore, it is worth knowing that any geologic correlation that is not consistent with the reservoir's physical properties will give a misrepresentation of different flow units. In constructing an appropriate model, it is important that both the " form" and " function" of the reservoir is honoured as much as possible. The form represents the geologic environment, rock type, and the reservoir architecture. The function represent the petrophysical properties that result in the flow performance. While the former is associated with the geologic zones, the latter on the other hand is associated with the quantitative statistical zonation. In the light of limited well data measured at representative sample point, a statistical technique is used to interpolate the unsampled spaces. Statistics, here provides the quantitative relationship describing the spatial variability of a reservoir property. A quantitative description of reservoir characteristics is necessary for proper statistical reservoir analysis. Quantification of these geological parameters statistically has become expedient in order to achieve a better reservoir zonation. Permeability of a rock is one of the most important flow parameter associated with sub-surface production and injection operations. The importance of the parameter is reflected by the number of sources - well logs, cores and well testing among others - that are employed to estimate permeability.

Geoscientists and reservoir engineers are very well acquainted with the terms "net-to-gross (NTG)" and "petrophysical cut-offs" or just "cut-offs". The significance of these terms is ultimately to define productive zones in the reservoir for hydrocarbon exploitation. However, there has been marked misunderstanding surrounding the usage of the term, net-to-gross and implicitly, the derivation of cut-offs which are limiting values used in expressing the net-to-gross ratio. While the geologist may be concerned with the pay for evaluating hydrocarbon-in-place and the ultimately the estimation of economically producible reserves, the simulation engineer is more concerned with fluid flow for pressure support in the reservoir. The significance of this paper is to consider the different cut-offs selection methods, the varying interpretation of net-to-gross ratios and the implications inherent in such methods. A case study from a field in the Niger Delta is also carried out to reveal the impact of such selection criteria especially in rocks with congenital weak hydraulic properties which cannot be excluded at geologic correlation stage. The effect of cut-off parameters on oil-initially-in-place (OIIP) calculation was also investigated and a sensitivity analysis carried out on the petrophysical parameters to reveal the impact of the dynamically conditioned cut-offs selection on the petrofacies. Multiple Monte Carlo realizations were also employed to obtain probabilistic OIIP estimates rather than a single deterministic result. Introduction Over the decades, the term net-to-gross and by extension, cut-offs have been extensively used in the oil industry especially by petrophysicists, reservoir geologists, and reservoir/simulation engineers. It is a basic reservoir parameter used for solving various problems ranging from OIIP calculations to reservoir flow simulation as one among several other variables to determine and predict reservoir performance. However there has been a great deal of confusion arising from the ways these parameters are defined, derived, and used. The fact actually is that it actually depends on the professionals involved, the circumstance of their usage, and the intended deliverables. Therefore, there have been no clear-cut definitions for these terms since most investigators do not explain the methodology involved in arriving at their own results. These have led to errors in areas of volumetric calculations, recovery factor calculations, welltest interpretations, stimulation design, and equity determination among others.

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