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1 1 Frontier and Basin Exploration

Published: 31 Mar 2019, 5:30 p.m. Revised: 2 Jun 2023, 5:15 p.m.

During basin-scale/frontier exploration, there is often uncertainty as to the presence, or not, of a carbonate platform or other carbonate strata in the subsurface. Often, poor quality seismic and an absence of local knowledge hinders confident identification and characterisation of carbonate strata. In the worst cases, structures are drilled and discovered to not be carbonate platforms, or indeed any form of potential reservoir (Burgess et al., 2013). It is possible to either fail to identify carbonate platforms, due to poor seismic data quality, or to incorrectly interpret positive structural features, eroded topographic features or palaeo-volcanic structures as carbonate platforms.

The focus of this workflow is on a) assessing the likelihood of carbonate presence and b) correctly mapping the size, distribution and geometry of the carbonate platform.

2 Stage 1 Review of basin evolution

Published: 21 Mar 2019, 2:48 p.m. Revised: 21 Mar 2019, 2:48 p.m.

The rationale behind the workflow for this phase of reservoir evaluation is to establish

a) the likelihood of carbonate strata development in the basin at a given point in the stratigraphy

b) assess whether a structure is likely to be a carbonate platform based on its shape, size, structural setting and seismic properties

c) if there is a high probability of a carbonate platform presence, present a range of appropriate reservoir analogues and

d) advise, based on a known set of structural, stratigraphic and sedimentological parameters, likely reservoir risks and opportunities for whatever carbonate strata may be present (eg. presence or absence of karst, presence or absence of dolostone).

The proposed workflow for each phase of work is outlined below, whilst details of the importance of determining individual parameters is described in the Appendices.

3 Stage 2 Seismic mapping of faults

Published: 21 Mar 2019, 2:51 p.m. Revised: 21 Mar 2019, 2:51 p.m.

The structural and stratigraphic framework of the basin is often a critical control on whether a carbonate platform becomes established, and where it grows. The starting point for seismic interpretation should therefore be an analysis of the literature on the region to determine plate- and basin-scale tectonic evolution. Guidance as to the importance of plate and basin-scale tectonics and stratigraphic age on the probability of carbonate platform development is given in Appendix I. In addition, examine the World Stress Map to assist in the interpretation of the effect of in situ stresses on the sealing capacity of the mapped faults.

4 Stage 3 Seismic interpretation of carbonate platforms

Published: 21 Mar 2019, 2:54 p.m. Revised: 21 Mar 2019, 2:54 p.m.

The identification of carbonate platforms on seismic data is inherantly challenging, because of poor quality imaging and the high potential for misinterpretion of high relief features, such as basement highs and volcanos, as carbonate platforms. The following workflow is modified from Burgess et al., 2013 (AAPG Bulletin) in order to improve confidence in carbonate platfom identification

5 Stage 4 Identification of Analogues

Published: 21 Mar 2019, 2:57 p.m. Revised: 21 Mar 2019, 2:57 p.m.

In order to improve confidence in seismic interpretation results, screening of potential outcrop and subsurface analogues is recommended using the Carbonate Reservoir Database

6 Stage 5 Forward Modelling

Published: 21 Mar 2019, 2:59 p.m. Revised: 30 Sep 2019, 11:22 a.m.

During appraisal, the absence of data from which facies architecture and diagenetic modification can be mapped means multiple scenarios can be envisaged to both explain platform evolution through time, and also the resultant reservoir properties. Stratigraphic forward models and reactive transport models therefore offer an opportunity by which the sensitivity of the platform to particular environmental parameters – and its resultant response – can be analysed.

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7 Stage 6 Screening Parameters

Published: 21 Mar 2019, 2:59 p.m. Revised: 21 Mar 2019, 2:59 p.m.

Once the Carbonate Reservoir Database has been reviewed, and analogues iterated with the seismic interpretation, the play should be de-risked with respect to reservoir presence, seal quality and the distribution of potential flow-controlling sedimentological, structural and diagenetic units.

8 Stage 1 Structural Evaluation

Published: 21 Mar 2019, 2:32 p.m. Revised: 2 Apr 2019, 8:07 p.m.

The rationale behind the workflow for this phase of reservoir evaluation is to refine estimates of in-place volumes and determine the reservoir recovery factor based on a range of potential recovery mechanisms. The workflow largely follows that defined for basin scale/frontier exploration, but assumes-

a) Prior analysis of basin formation mechanism, tectonostratigraphy and palaeo-plate reconstruction

b) A richer dataset, for example reprocessed seismic data, well data and/or more evolved analogue studies

c) A larger, more multi-disciplinary team, including petrophysicists, reservoir engineers and well & production engineers

9 Stage 2 Seismic interpretation of carbonate platforms

Published: 2 Apr 2019, 8 p.m. Revised: 2 Apr 2019, 8 p.m.

This workflow resembles that used for frontier exploration, but assumes that the presence of a carbonate platform has been confirmed, data quality is higher and more well data is available for calibration. It also assumes that fault mapping has been refined.

10 Stage 3 Sedimentological and diagenetic interpretation of well data

Published: 2 Apr 2019, 8:05 p.m. Revised: 2 Apr 2019, 8:05 p.m.

If core is available during appraisal, then it should be optimised for geological interpretation. It is expected that this will be conducted partly in parallel with core petrophysical analysis, although there is value in ensuring the routine core petrophysical data is used to select samples for petrographical anlaysis.

11 Stage 4 Petrophysical Analysis

Published: 21 Mar 2019, 2:37 p.m. Revised: 21 Mar 2019, 2:37 p.m.

Petrophysical analysis involves the integration of core, log and seismic data to determine the volume and distribution of porosity, saturation, net reservoir and permeability. During appraisal, it is assumed there are only 1-2 wells available with data, and possibly no core data.

12 Stage 5 Interpretations

Published: 21 Mar 2019, 2:38 p.m. Revised: 21 Mar 2019, 2:38 p.m.

Once core description, wireline log analysis and seismic interpretation has been conducted, the spatial distribution of facies and diagenetic overprint can be assessed and their impact on petrophysical properties interpreted.

13 Stage 6 Forward Modelling

Published: 21 Mar 2019, 2:11 p.m. Revised: 21 Mar 2019, 2:41 p.m.

During appraisal, the absence of data from which facies architecture and diagenetic modification can be mapped means multiple scenarios can be envisaged to both explain platform evolution through time, and also the resultant reservoir properties. Stratigraphic forward models and reactive transport models therefore offer an opportunity by which the sensitivity of the platform to particular environmental parameters – and its resultant response – can be analysed.

14 Stage 7 Reservoir modelling

Published: 21 Mar 2019, 2:21 p.m. Revised: 21 Mar 2019, 2:42 p.m.

Reservoir models are critical to concept testing and selection for field development, including optimisation of well placement and analysis of full-field economics. In order that the most economically and technically feasible development option is selected, it is imperative that reservoir models are

a) constructed using geologically robust rules sets, providing confidence in interwell permeability prediction

b) have appropriately upscaled petrophysical properties, so that flow controlling layers are not obscured by averaging

c) have assigned dynamic data (e.g. relative permeability) that reflects, rather than obscures, reservoir heterogeneity

d) able to incorporate past and present reservoir performance within the geological interpretation, so that flow-controlling layers (e.g. baffles, barriers and high permeability streaks) are represented in the model, and

e) fundamentally linked to a fracture model

A range of geostatistical methods can be used for modelling carbonate reservoir architecture. None are used consistently by the industry, and the modelling workflow is often driven by corporate workflows (perhaps based on clastic reservoirs), reservoir architectural elements, data type, quality and volume, the timeframe available for model construction and prior experience of the reservoir modeller.

Once faults have been picked, surfaces mapped and the model grid constructed, most carbonate reservoirs should be modelled by a workflow that includes facies modelling, diagenetic modelling, petrophysical modelling and fracture modelling. However, during appraisal, it is unlikely that there will be sufficient data for this workflow to be developed in full. At this point it is more important to undertake a robust risk and uncertainty analysis and thereby assess the impact of these uncertainties by running multiple scenarios. One approach for ensuring that the most appropriate range of scenarios is modelled, taking account of the combined uncertainty of different parameters, is through experimental design (e.g. Hollis et al., 2011).

15 Stage 1 Data collation, QC and analysis

Published: 21 Mar 2019, 3:07 p.m. Revised: 21 Mar 2019, 3:07 p.m.

Many mature fields have a poor or disparate historical dataset, particularly with respect to core. Even where there has been diligent data collection, the varying vintages of core and log material, as well as a succession of different interpreters, alongside changing scientific paradigms might mean that there is a confusing, inconsistent opinion as to the origin and dimensions of geological parameters. Often there are perceptions as to why a field performs as it does which are not founded on systematic data collection and analysis. Consequently, prior to a full field re-evaluation of development strategy, a period of intense data collection and analysis is strongly recommended.

16 Stage 2 Structural framework

Published: 21 Mar 2019, 3:08 p.m. Revised: 21 Mar 2019, 3:08 p.m.

The aim of this phase of work is to ensure that the structural evolution of the carbonate platform is understood as completely as possible. This includes the style and timing of faulting, the relationships between faulting, burial and fracture distribution, and the timing of hydrocarbon charge

17 Stage 3 Sedimentological Analysis

Published: 21 Mar 2019, 3:10 p.m. Revised: 21 Mar 2019, 3:10 p.m.

Normally during appraisal, reservoir architecture is established in the context of basin-scale sequence stratigraphy. This will have been driven largely by seismic data, with limited well calibration. With the addition of well data during appraisal and development drilling, this sedimentological interpretation can be revisited using the well and core interpretation workflows

18 Stage 4 Diagenesis

Published: 21 Mar 2019, 3:13 p.m. Revised: 21 Mar 2019, 3:13 p.m.

Many reservoirs do not have a detailed conceptual model to explain the character and distribution of the diagenetic overprint and how it has influenced reservoir properties, even though most carbonate reservoirs have undergone sufficient diagenesis to significantly alter reservoir properties. Although sedimentary facies (associations) often form a template for diagenetic modification, porosity and permeability are typically also strongly influenced by dolomitization, cementation, post-depositional dissolution and/or fracturing. However, in the absence of clear workflows to link depositional rock properties to reservoir properties, and without guidelines for construction of diagenetic overprint within geocellular models, this phase of the workflow is often overlooked.

19 Stage 5 Petrophysical analysis

Published: 21 Mar 2019, 3:18 p.m. Revised: 21 Mar 2019, 3:18 p.m.

The aim of this phase of work is to group data into clusters of genetically associated rock types (i.e. mappable units which have evolved via the same depositional and diagenetic pathways) with consistent petrophysical properties. The process relies heavily on prior determination of a robust diagenetic framework and should build on data collected during Stages 1 and 2.

20 Stage 6 Reservoir modelling

Published: 21 Mar 2019, 3:23 p.m. Revised: 21 Mar 2019, 3:23 p.m.

Reservoir models are critical to concept testing and selection for field development, including optimisation of well placement and analysis of full-field economics.