SAGD Reservoir Characterization Considerations – Part 1
WRITTEN BY: MARK SAVAGE APEGA P.L. Geo. member
The reservoir characterization process (the process) is the foundation for subsurface deliverables. The extent of the detail and focus areas required for the process are influenced by the overall project scope, schedule, and budget. The process should incorporate cross-functional (finance, facilities, etc.) and multidisciplinary (geoscience, reservoir engineering, etc.) input.
This process has been used for a range of project decisions, up to significant decision gate (DG) milestones, DG1 (concept), DG3 (sanction), Figure 1, and resource and reserve determination and validation.
Figure 1 Simplified Decision Gate Example (Source: Savage, M., 2020)
By following this process, a thorough understanding of the steam-assisted gravity drainage (SAGD) asset potential and uncertainty can be gained. With some minor modifications, the workflow and considerations could be used across different asset types.
A vital component of the process is multidisciplinary collaboration. As a minimum, the following disciplines should be involved: geology, geophysics, petrophysics, geomodelling, and reservoir/production engineering. Depending on the project specifics, other cross-functional disciplines may be required: field operations, facilities, project engineering, drilling and completion engineering, risk analyst, and finance.
There are three stages to the process workflow: data collection and geoscience analysis, petrophysical analysis and geomodel development, Figure 2. The 3-D geomodel and simulations are dynamic and may need updates from new learnings and information.
Figure 2 Reservoir Characterization Workflow (Source: Savage, M., 2020)
Each stage of this workflow will influence the degree of uncertainty captured in the performance predictions. These predictions are used to assess volumetrics, greenfield or brownfield optimal facility design capacity, number of wells required for a field or pad start-up, and the schedule for production rate sustaining pads. The schedule should incorporate performance learnings and required modifications from the producing pads, e.g. updated 3-D geomodels, type curves, and simulations.
This commentary is part one of a two-part paper and addresses the data collection component of the process. Part two of the paper will address the petrophysical analysis and geomodelling components of the process.
Data Acquisition and Geoscience Analysis
The purpose of completing the process is to evaluate and identify subsurface opportunities and risks. The acquisition of subsurface data is a fundamental component in the process. Collection of reservoir data relevant to the extraction technology used is critical.
The process relies on data derived from multiple sources: openhole and cased hole logs, geological core description and analysis, outcrop data, lab tests and seismic (2-D, 3-D or 4-D). This data is used to quantify and qualify key micro, macro and mega-scale reservoir parameters, such as permeability, relative permeability, grain size, reservoir facies, bitumen geochemistry, geobody dimensions, clay mineralogy, porosity, and saturation.
Interpretation of these data sets are required to capture the variance and uncertainty associated with reservoir heterogeneity.
Figure 3 Openhole Wireline Logs with Core Information (Source: AER D54 2019 11387)
Openhole and Cased Hole Log Data
All wells drilled to assess a reservoir should have openhole wireline logs run to measure critical in-situ parameters (porosity and saturation), Figure 3. Depending on the basin’s exploration history, there may be different vintages and log data quality. Normalization of the log data in the petrophysical stage is critical. This data becomes input parameters for the 3-D geomodel, for the reservoir volumetrics and simulation.
A few of the planned strat wells should be considered as observation well (Obs) candidates. Obs wells facilitate collection of real-time temperature and/or pressure data during the production phase, Figure 4. These Obs wells can also collect cased hole log data throughout the production life cycle. Obs well data can be used to calibrate both 4-D seismic and simulations, update resource and reserve estimates, and to revise the drilling, construction and the production schedules of the sustaining pads.
Figure 4 Obs Well Temperature (red colour fill) and Pressure Data (blue colour fill) (Source: AER D54 2019 11387)
A cost-saving consideration for the openhole logging program is the addition of borehole image logs. This tool obtains in-situ reservoir information while eliminating the cost to core wells beyond the Alberta Department of Energy Oil Sands Minimum Lease Evaluation continuation requirements. Borehole image log data should be calibrated by running the log in several cored wells.
Technical justification for running borehole image logs is the capability to consistently assess reservoir facies, identify faults/fractures and measure dip angle direction. This data, combined with bitumen geochemistry, can aid in analysis of potential reservoir baffles or barriers. The dip direction data can influence the optimal position and orientation of SAGD well placement.
Ensure that the first producing pads have enough core and borehole image log data points to represent the critical reservoir facies. Add reservoir insight by targeting anomalous features on 3-D seismic with core or borehole image logs in planned strat wells.
Optimal data collection could include:
- Cased hole wireline saturation logs, baseline saturation survey is acquired before first steam;
- Petrophysical comparison and calibration of the openhole and cased hole saturation data to identify variances: and
- The first repeat log acquisition is typically 12 – 18 months after initial production and is influenced by Obs well distance from the SAGD well pair.
Figure 5 Obs Well Cased Hole Saturation Log and Temperature Data (Source: AER D54 2020 11888)
The steam chamber is defined by the convective heating zone, Figure 5. The conductive heating zone is defined by the warmed bitumen above the steam chamber. Production induced saturation changes, growth of the steam chamber, and the advancing “gas phase” are apparent with repeat acquisitions of the cased hole saturation logs.
The saturation log data and learnings from repeat acquisitions can be used to calibrate 4-D seismic and modify future 3-D geomodels and simulations.
It is essential that the data from openhole and cased hole logs are normalized and calibrated. Interpretation of the log data should be vetted for consistency before using it in the 4-D seismic interpretations and generating updated 3-D geomodel realizations.
Core and Outcrop Data
A key piece of data is representative core from the reservoir and field, Figure 6.
Figure 6 Oil Sands Core Photo Example (Source: AER D54 2019 8870)
A crucial factor in the process is to ensure care is taken in cutting and transportation of the core to facilitate laboratory testing. The appropriate coring procedure should be determined by the multidisciplinary team and the service providers before finalizing the acquisition and testing program.
There are two types of core analysis generally conducted: routine and special core analysis (SCAL).
There are several routine core analyses (oil saturation, permeability, etc.) conducted to evaluate reservoir potential and risk. Essential core derived data sets are Dean-Stark oil saturation, grain size, mud volume, porosity and permeability. Saturation and permeability are strong indicators of reservoir performance potential. The openhole wireline saturation data should be calibrated with the core derived saturation data.
Another routine piece of data is the digital core photographs. These photographs, combined with the wireline logs and the core, are used to describe and interpret reservoir features, such as depositional environment, bedding, facies, fractures, faults and the degree of bioturbation. These features aid in quantifying the reservoir quality, risks and in the identification of geobodies.
The geological reservoir facies typically used to describe SAGD reservoirs is a proxy for vertical permeability and is based on mud bed volume, not to be confused with interstitial clay content. Each SAGD operator has their own facies scheme, Figure 7, but the principle is the same, the lower the mud bed volume, the better the vertical permeability. A facies scheme is developed from the core, borehole image logs and the wireline logs.
Figure 7 SAGD Facies Scheme (Source: AER D54 2019 8668)
When conducting Kv SCAL tests, ensure that key reservoir facies are represented, including Inclined Heterolithic Stratification (IHS) units. The most effective Kv samples are taken from a full diameter core kept at ambient conditions (not frozen). Conducting Kv tests at operational conditions can provide additional information relevant to understanding ultimate recovery potential. This Kv data is fundamental to reservoir simulation.The SAGD process is heavily influenced by saturation and permeability, and most importantly, vertical permeability. Vertical permeability (Kv) is directly influenced by micro and macro-scale parameters: pore throat geometry, grain size distribution, clay type, bioturbation and the presence of mud beds. The horizontal continuity of mud beds is challenging to quantify (fluvial vs. estuarine vs. marine environments) and can be the most influential parameter on performance.
Two SCAL tests that are influential in reservoir simulation are relative permeability and pressure-volume-temperature (PVT) analysis. Reservoir engineering input is essential to discussions and decisions of relative permeability and PVT analysis, e.g. the number of samples per facies, sample location and test conditions (temperature, pressure, pore volumes, etc.).
Clay mineralogy can be valuable data. Specifically, the volume and location of swelling clays, in the context of the reservoir’s depositional environment. Understanding clay mineralogy can assist quantifying the risk of reduced permeability from formation damage, induced by drilling fluid and/or injected fluids used for enhanced oil recovery.
A SCAL test of considerable value is bitumen geochemical analysis using core samples along the vertical profile of the reservoir. A bitumen geochemical profile can aid in identifying a baffle versus a barrier and potential impact on steam chamber development. This data may be integral to the 3-D geomodel and simulation outcomes.
Lastly, a valuable part of the routine analysis is grain size analysis. Grain size analysis data is needed for consideration of sand control in the well design. Grain size distribution can be measured using one of two methods: sieve or laser analysis. Regardless, the method selected should be the same methodology used for future grain size analysis in the same pool. Readily available grain size samples can come from Dean-Stark retains. For SAGD projects, the basal 10 meters of pay need to be sampled, because this is where the production and injection well pair is positioned.
Figure 8 Steepbank McMurray Outcrop (Source: flickr Luck, R., June 2005)
Data that is sometimes overlooked is outcrop data analogous to the reservoir. Outcrop data may provide reservoir specific areal information that can be incorporated into geological interpretations and 3-D geomodels. Outcrop features such as continuity of mud beds, and lateral continuity of reservoir facies are key, Figure 8. This information may be used to assist in understanding and defining geologic baffles or barriers.
It is critical that the data and interpretations from core analysis are checked and cleaned before use in the workflow. The statement “garbage in, garbage out” is true in this process.
Geophysics is essential to interpretation, evaluation, geomodeling and reservoir management. Seismic data is unique in the 3-D and 4-D perspective it provides, making it both a supplemental and complementary data source.
The advantage of 3-D seismic is the vertical and areal coverage it provides across a pad or an entire development area. This scale of areal coverage is superior to other data sources and can identify reservoir features not encountered by the strat well program. Seismic is particularly useful in defining reservoir features with a distinct geophysical characteristic such as:
- continuity of mud dominant intervals;
- potential thief zones (low-pressure gas);
- mud-filled abandonment channels; and
- other impediments to SAGD development.
These geophysical learnings can be incorporated into a 3-D geomodel as either a hard surface or a soft trend, e.g. influencing geobody vertical or areal distribution. This will result in a 3-D geomodel that captures distinctive subsurface features that influence performance predictions and the range of uncertainty.
Once the SAGD asset has been producing, 4-D seismic at selected periods over the asset’s life can provide further learnings into the steam chamber development.
Adding periodic repeat surveys to seismic acquisition enables an ability to track, measure and monitor the steam chamber development over time, Figure 9. Note the increased conformance indicated by the reduction in gray coloured areas, from 2006 to 2012. This dynamic 4-D data can provide insight into the parameters used in facies definitions, and if a revision to facies scheme, 3-D geomodel and production simulation is warranted.
Figure 9 4-D Seismic Time-lapse Example (Source AER D54 2015 8870)
Data collection directly impacts the quality of results in the reservoir characterization process. Spending adequate time to plan the data collection stage, and to facilitate contributions from multidisciplinary and cross-functional groups, including the service providers in the program design ensures an optimal reservoir characterization process. The integration of these different data sources will result in enhanced interpretations, in the generation of better geomodels and more representative production simulations.
Mark Savage, APEGA P.L. Geo. member, has been in the oil sands industry since 2000. Mark started his oil sands career with Petro-Canada working on the Lewis, MacKay River and Fort Hills projects. Since leaving Petro-Canada in 2008, he has been actively engaged in various in-situ oil sands assets with Ivanhoe Energy Ltd., Statoil Canada Ltd. and Athabasca Oil Corp. He has collaborated on and led in-situ geoscience, operations and development teams.