14th June 2016
Unconventional reservoirs present many technical challenges to those charged with quantifying reservoir character and performance (Bust, Majid, Oletu & Worthington 2013). One of these challenges concerns the identification of net pay. The role of net pay in unconventional reservoirs continues to evolve as a design criterion for reservoir stimulation and well completions. Unlike conventional reservoirs, shale-gas development is not yet at the stage where longstanding net-pay protocols have been tried and tested. Therefore, any protocol has to be regarded as being at a pilot stage, especially in view of the complexity of shale-gas systems.
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The concepts of net reservoir and net pay co-exist in conventional reservoirs, for which volumetric computations have drawn upon both. In shale gas reservoirs, which also act as source and seal, net reservoir is subordinate to net pay, because a penetrated interval is of interest only where it contains producible hydrocarbons.
Net pay is generally defined as a penetrated thickness of reservoir rock that contains hydrocarbons in sufficient quantities to be of potential interest. In conventional reservoirs, economic viability is often considered at the zonal or field scale. In shale-gas reservoirs, economic viability has to be considered at the well scale, because of limited connectivity between wells, and therefore net pay should be defined as penetrated thickness of reservoir rock that contains hydrocarbons whose production is economically viable. The identification of net pay is a petrophysical exercise that is primarily based on well logs with some supporting core data. The aim is to set up a core-calibrated log-derived pay recognition system based upon key wells with comprehensive logging and core data and then to export this to uncored wells that have been logged with a basic suite, i.e. one that is sufficient for pay recognition but contains no extra tools.. This objective is challenged by the marked heterogeneity of shale-gas deposits.
Ideally, the quantification of net pay should be driven by data.There is no industry-standard way of doing this even for conventional reservoirs, which have a long history of evaluation. For shale-gas reservoirs, there needs to be some further set of concepts to take account of those factors that have the greatest bearing on net pay. Examples are the host rock acting as a sandy shale rather than a conventional shaly sand and also the concept that net pay should be reported as along hole rather than in true vertical depth as is the case in conventional reservoirs.
Net Pay Discriminators and Cut-Offs
Net pay is identified through discriminators, which are parameters that relate to the storage and flow of hydrocarbons within a host rock. Conventional discriminators cannot be exported directly to unconventional reservoirs. However, it is possible to draw upon conventional experience when formulating net pay criteria for shale-gas reservoirs. In general, it is good practice to adopt the minimum number of net pay discriminators that guarantees functionality. These matters are reflected in Fig. 1, which shows a broad correspondence between conventional net pay discriminators and a minimalistic set that is appropriate to shale-gas reservoirs. Shale gas discriminators must address flow capability, the source rock potential and the capacity of the shale and kerogen matrices for gas storage.
Figure 1: Correspondence of conventional and shale-gas net-pay discriminators
Net-pay cut-offs are quantitative values of discriminators that define the ranges of rock property values over which a host rock has sufficiently good reservoir properties and contains sufficient hydrocarbons to be of potential economic interest (Worthington & Cosentino 2005). They are applied to well logs after having been quantified using core and cuttings data. It is important that such core analysis be conducted on data that have been upscaled to the well-log scale. Otherwise the empirical cut-offs may turn out to be inappropriate. Cut-offs are data-driven and therefore they can vary in response to changes in rock character. This means that different sets of cut-offs can apply to different geological/petrophysical zones or to diverse partitioned datasets. Cut-offs can be classified as “less-than” or “greater-than-or-equal-to” cut-offs according to the discriminator used.
For shale-gas reservoirs, the most important requirement is to establish through total organic carbon (TOC) and source rock characterization that oil-prone kerogen is present in sufficient concentrations. Oil-prone, rather than gas-prone kerogen is generally required to provide sufficient hydrocarbon concentration to be commercially attractive. Note that the entire interval must be at an optimum level of thermal maturity to balance the generation of gas-phase hydrocarbons with their retention in the source rock without significant expulsion. Clearly, if TOC is zero, kerogen content will be zero and net pay will be set at zero.
The second requirement is to identify the along-hole kerogen-bearing intervals that can be usefully fractured based on brittleness and with reference to natural fracture density. Brittleness can be defined formally in terms of rock physical properties or, more pragmatically by mineralogical ratios that emphasize the presence or quartz, or quartz and dolomite, over clays, other carbonates, and organic material.
The third requirement is to identify those intervals that have a functional porosity, which is referenced to permeability to reflect the storage and transmissive character of a reservoir rock. Finally, the presence of a supracritical gas saturation is determined from resistivity and/or other logs such as magnetic resonance imagers. Complexity will be introduced by the need to clearly discriminate the petrophysical effects of abundant kerogen in the rock from those of generated hydrocarbons, using an array of additional geochemical techniques. It may also be necessary to include a consideration of a sorbed as well as free gas component for certain, shallow gas plays. These matters are summarized in Table 1, which relates cut-off parameters to the terminology of Fig. 1.
Table 1: Relationship of cut-off parameters to net intervals.
Table 2 lists some generic cut-off values, which could be used where no formation-specific cut-offs could be discerned. The primary cut-offs are key. The secondary cut-offs provide essential input once a favorable primary setting has been identified. The cut-offs of Table 2 are not data-driven. They should be superseded if and when formation-specific data become available. Note that a proxy cut-off is often used as many direct measurements of critical primary discriminators, for example rock strength and physical moduli, or permeability, are costly and may be carried out on relatively few representative samples. This approach makes use of a different discriminator whose cut-off value is tied back to that of the primary discriminator. As an example, in the Antrim Shale of the Michigan Basin (Decker, Hill & Wicks 1993), bulk density was plotted against TOC, with the bulk density that corresponds to a TOC of 2.0 weight % (cf Table 2) being determined as a proxy density cut-off for TOC. Other functional examples can be found in the literature. Table 2 also lists a proposed range of uncertainty for each of the generic cut-offs. These are notionally founded on key-well data that allow the interpretation of a full suite of characterizing well logs to be groundtruthed by core analysis.
Table 2: Generic cut-offs
Fig. 2 shows a high-level technical workflow for the identification of net pay in shale-gas reservoirs. The setting is that of a key well. The aim is to use key-well data to establish values of the cut-off parameters listed in Table 1 and then to export these cut-offs to non-key wells that are uncored/unsampled and have been logged with a less extensive suite. Fig. 2 identifies the ideal logs to be run in a key well, the interpretative deliverables, and how these relate to net intervals. Fig. 2 also broadly ranks the relative importance of core analysis in support of well-log interpretation.
Fig 2: High-level workflow for the identification of net pay at a key well within a shale-gas reservoir.
An important difference between the application of cut-off criteria in conventional and shale-gas reservoirs lies in the approach to horizontal wells. For conventional reservoirs, the role of net pay is often driven by field volumetrics and is notionally reported in true vertical space. However, along-hole net pay does serve as a guide to well completions. For shale-gas reservoirs, which act as source, seal and reservoir, the application of net-pay concepts is substantially directed at well completions, so along-hole net pay is the primary reference. This means that where net pay is based on cut-offs of directionally-dependent parameters such as permeability and stress, some account should be taken of how the application of these parameters changes with well deviation. Such a task is compounded by the heterogeneity of shale-gas reservoirs, which may impede definitive directional analysis. Moreover, the exercise is impacted by the relative dearth of core and log data from horizontal wells vis-à-vis vertical wells.
Viewed overall, the evaluation of shale gas reservoirs remains on a steep learning curve and this is likely to be the case for some time to come.
This article is extracted , with some amendment, from a paper published by Paul F. Worthington & Azlan A. Majid, Journal of Petroleum Science and Engineering, vol. 120, pp 78-85 (2014).
Bust, V.K., Majid, A.A., Oletu, J.U. & Worthington, P.F. 2013. The petrophysics of shale gas reservoirs: technical challenges and pragmatic solutions. Petroleum Geoscience, 19, 91-103.
Decker, A.D., Hill, D.G. & Wicks, D.E. 1993. Log-based gas content and resource estimates for the Antrim Shale, Michigan Basin. SPE Paper 25910, Society of Petroleum Engineers, Richardson, Texas.
Worthington, P.F. & Cosentino, L. 2005. The role of cut-offs in integrated reservoir studies. SPE Reservoir Evaluation and Engineering 8, 276-290.
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