CO2 Storage Site Screening Platform Development and CO2 Storage Resource Analysis in SECARB Offshore Reservoirs Using SAS Viya

Cap rock integrity is an essential characteristic of any reservoir to be used for long-term [Formula: see text] storage. Seismic AVOA (amplitude variation with offset and azimuth) techniques have been applied to map HTI anisotropy near the cap rock of the Weyburn field in southeast Saskatchewan, Canada, with the purpose of identifying potential fracture zones that may compromise seal integrity. This analysis, supported by modeling, observes the top of the regional seal (Watrous Formation) to have low levels of HTI anisotropy, whereas the reservoir cap rock (composite Midale Evaporite and Ratcliffe Beds) contains isolated areas of high intensity anisotropy, which may be fracture-related. Properties of the fracture fill and hydraulic conductivity within the inferred fracture zones are not constrained using this technique. The predominant orientations of the observed anisotropy are parallel and normal to the direction of maximum horizontal stress (northeast–southwest) and agree closely with previous fracture studies on core samples from the reservoir. Anisotropy anomalies are observed to correlate spatially with salt dissolution structures in the cap rock and overlying horizons as interpreted from 3D seismic cross sections.

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Assessing the Accuracy of Fault Interpretation using Machine Learning Techniques when Risking Faults for CO2 Storage Site Assessment

Interpretation ◽

10.1190/int-2021-0077.1 ◽

2021 ◽

pp. 1-55

Author(s):

Emma A. H. Michie ◽

Behzad Alaei ◽

Alvar Braathen

Keyword(s):

Deep Learning ◽

New Technologies ◽

Co2 Storage ◽

Fault Reactivation ◽

Machine Learning Techniques ◽

Close Similarity ◽

Storage Site ◽

Site Assessment ◽

Learning Techniques ◽

Fault Interpretation

Generating an accurate model of the subsurface for the purpose of assessing the feasibility of a CO2 storage site is crucial. In particular, how faults are interpreted is likely to influence the predicted capacity and integrity of the reservoir; whether this is through identifying high risk areas along the fault, where fluid is likely to flow across the fault, or by assessing the reactivation potential of the fault with increased pressure, causing fluid to flow up the fault. New technologies allow users to interpret faults effortlessly, and in much quicker time, utilizing methods such as Deep Learning. These Deep Learning techniques use knowledge from Neural Networks to allow end-users to compute areas where faults are likely to occur. Although these new technologies may be attractive due to reduced interpretation time, it is important to understand the inherent uncertainties in their ability to predict accurate fault geometries. Here, we compare Deep Learning fault interpretation versus manual fault interpretation, and can see distinct differences to those faults where significant ambiguity exists due to poor seismic resolution at the fault; we observe an increased irregularity when Deep Learning methods are used over conventional manual interpretation. This can result in significant differences between the resulting analyses, such as fault reactivation potential. Conversely, we observe that well-imaged faults show a close similarity between the resulting fault surfaces when both Deep Learning and manual fault interpretation methods are employed, and hence we also observe a close similarity between any attributes and fault analyses made.

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How Chosen Seismic Fault Picking Strategy Influences Subsequent Fault Analyses: A Case Study from the Horda Platform, with Implications for CO2 storage

10.5194/egusphere-egu21-1217 ◽

2021 ◽

Author(s):

Emma Michie ◽

Mark Mulrooney ◽

Alvar Braathen

Keyword(s):

Fluid Flow ◽

Co2 Storage ◽

Fault Analysis ◽

Surface Generation ◽

Storage Site ◽

Seismic Line ◽

Fault Stability ◽

Line Spacing ◽

Fault Growth

Significant uncertainties occur through varying methodologies when interpreting faults using seismic data.&#160; These uncertainties are carried through to the interpretation of how faults may act as baffles/barriers or increase fluid flow.&#160; Seismic line spacing chosen by the interpreter when picking fault segments, as well as the chosen surface generation algorithm used, will dictate how detailed or smoothed the surface is, and hence will impact any further interpretation such as fault seal, fault stability and fault growth analyses.This contribution is a case study showing how picking strategies influence analysis of a bounding fault in terms of CO2 storage assessment.&#160; This example utilizes data from the Smeaheia potential storage site within the Horda Platform, 20 km East of Troll East.&#160; This is a fault bound prospect, known as the Alpha prospect, and hence the bounding fault is required to have a high seal potential and low chance of reactivation upon CO2 injection.We can observe that an optimum spacing for fault interpretation for this case study is set at approximately 100 m.&#160; It appears that any additional detail through interpretation with a line spacing of &#8804;50 m simply adds further complexities, associated with sensitivities by the individual interpreter.&#160; Hence, interpreting at a finer scale may not necessarily improve the subsurface model and any related analysis, but in fact lead to the production of highly irregular surfaces, which impacts any further fault analysis.&#160; Interpreting on spacing greater than 100 m often leads to overly smoothed fault surfaces that miss details that could be crucial, both for fault seal / stability as well as for fault growth models.Uncertainty associated with the chosen seismic interpretation methodology will follow through to subsequent fault seal analysis, such as analysis of whether in situ stresses, combined with increased pore pressure through CO2 injection, will act to reactivate the faults, leading to up-fault fluid flow / seep.&#160; We have shown that changing picking strategies significantly alters the interpreted stability of the fault, where picking with an increased line spacing has shown to increase the overall fault stability, and picking using every line leads to the interpretation of a critically stressed fault.&#160; Alternatively, it is important to note that differences in picking strategy show little influence on the overall predicted fault membrane seal (i.e. shale gouge ratio) of the fault, used when interpreting the fault seal capacity for a fault bound CO2 storage site.

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