Added Value by Fast and Robust Conditioning of Structural Surfaces to Horizontal Wells for Real-World Reservoir Models

Stenerud, Vegard R.; Kallekleiv, Hans; Abrahamsen, Petter; Dahle, P.; Skorstad, A.; Viken, May Hege Aalmen

doi:10.2118/159746-ms

Cited by 6 publications

(4 citation statements)

References 10 publications

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“…In [32] workflow is that multiple model realizations can be automatically generated in batch and in parallel, in a fully reproducible manner. In [34] it is discussed how the geometry and depth of a stack of stratigraphic interfaces can be modified in a geologically realistic manner. In [33] it is explained that for each realization of the earth model grid, all individual modelling steps are still performed as in the conventional modelling process.…”

Section: A3 Current Methods For Earth Modellingmentioning

confidence: 99%

A Novel Method for Locally Updating an Earth Model While Geosteering

Suter¹,

Cayeux²,

Friis³

et al. 2017

IJG

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Earth models are important tools for support of decision making processes for optimal exploitation of subsurface resources. For geosteering and other realtime processes where time is a major constraint, effective model management is decisive for optimal decision support. During drilling, subsurface information is received which should optimally be used to modify the 3D earth model. Today this model is typically not altered during the operation. We discuss the principles of a novel method that enables a populated earth model grid to be locally modified when the topology (connectivity) of the geological structure is locally altered. The method also allows local updates of the grid resolution. The modelled volume is split into closed regions by the structural model. Each region is individually discretized and obtains its own subgrid. Properties are stored in separate functions, e.g. for each layer, and transferred into each subgrid via a mapping. A local update of the geological structure implies that only subgrids in regions that are directly affected by the updated structure must be discarded and rebuilt, and the rest of the populated earth model grid is retained. Our focus is on decision support for optimal well placement while geosteering. The proposed method aims to manage multiple model realizations that are never fixed and always locally updated with the most recent measurements and interpretations in real-time, and where each realization is always kept at an optimal resolution.

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Section: A3 Current Methods For Earth Modellingmentioning

confidence: 99%

A Novel Method for Locally Updating an Earth Model While Geosteering

Suter¹,

Cayeux²,

Friis³

et al. 2017

IJG

View full text Add to dashboard Cite

show abstract

“…Uncertainty associated with wells comes from the well position, well trajectory and interpretation of well picks (markers, well tops) (Stenerud et al, 2012;Howley and Meyer, 2015;Pakyuz-Charrier et al, 2018). Particularly, capturing well uncertainty is challenging in reservoirs with multiple horizontal wells, where the adjustment of horizons to honor well information is often in conflict.…”

Section: Introductionmentioning

confidence: 99%

“…The integrated modeling workflows presented in Leahy and Skorstad (2013), Aarnes et al (2014), and Howley and Meyer (2015) are capable of capturing uncertainties associated with any property and step of the modeling workflow. These workflows have evolved from methodologies described in MacDonald et al (2009), Skjervheim et al (2012) and Stenerud et al (2012), and in turn integrate algorithms for the horizon simulation based on a Bayesian statistical approach by Abrahamsen (1993Abrahamsen ( , 2005 and Abrahamsen and Benth (2001).…”

Section: Introductionmentioning

confidence: 99%

Quantifying the impact of the structural uncertainty on the gross rock volume in the Lubina and Montanazo oil fields (Western Mediterranean)

Bárbara¹,

Cabello

Bouche

et al. 2019

Solid Earth

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Abstract. Structural uncertainty is a key parameter affecting the accuracy of the information contained in static and dynamic reservoir models. However, quantifying and assessing its real impact on reservoir property distribution, in-place volume estimates and dynamic simulation has always been a challenge. Due to the limitation of the existing workflows and time constraints, the exploration of all potential geological configurations matching the interpreted data has been limited to a small number of scenarios, making the future field development decisions uncertain. We present a case study in the Lubina and Montanazo mature oil fields (Western Mediterranean) in which the structural uncertainty in the seismic interpretation of faults and horizons has been captured using modern reservoir modeling workflows. We model the fault and horizon uncertainty by means of two workflows: the manually interpreted and the constant uncertainty cases. In the manually interpreted case, the zones of ambiguity in the position of horizons and faults are defined as locally varying envelopes around the best interpretation, whose dimensions mainly vary according to the frequency content of the seismic data, lateral variations of amplitudes along reflectors, and how the reflectors terminate around faults when fault reflections are not present in the seismic image. In the constant case, the envelope dimensions are kept constant for each horizon and each fault. Both faults and horizons are simulated within their respective uncertainty envelopes as provided to the user. In all simulations, conditioning to available well data is ensured. Stochastic simulation was used to obtain 200 realizations for each uncertainty modeling workflow. The realizations were compared in terms of gross rock volumes above the oil–water contact considering three scenarios at the depths of the contact. The results show that capturing the structural uncertainty in the picking of horizons and faults in seismic data has a relevant impact on the volume estimation. The models predict percentage differences in the mean gross rock volume with respect to best-estimate interpretation up to 7 % higher and 12 % lower (P10 and P90). The manually interpreted uncertainty workflow reports narrower gross rock volume predictions and more consistent results from the simulated structural models than the constant case. This work has also revealed that, for the Lubina and Montanazo fields, the fault uncertainty associated with the major faults that bound the reservoir laterally strongly affects the gross rock volume predicted. The multiple realizations obtained are geologically consistent with the available data, and their differences in geometry and dimensions of the reservoir allow us to improve the understanding of the reservoir structure. The uncertainty modeling workflows applied are easy to design and allow us to update the models when required. This work demonstrates that knowledge of the data and the sources of uncertainty is important to set up the workflows correctly. Further studies can combine other sources of uncertainty in the modeling process to improve the risk assessment.

show abstract

“…The integrated modeling workflows presented in Leahy and Skorstad (2013), Aarnes et al (2014) and Howley and Meyer (2015) are capable to capture uncertainties associated to any property and step of the modeling workflow. These workflows have evolved from methodologies described in MacDonald et al (2009), Skjervheim et al (2012), Stenerud et al (2012), and in turn integrate algorithms for the horizon simulation based on a Bayesian statistical approach by Abrahamsen (1993), Abrahamsen (2005) and Abrahamsen and Benth (2001).…”

Section: Introductionmentioning

confidence: 99%

Quantifying the impact of the structural uncertainty on the gross rock volume in the Lubina and Montanazo oil fields (Western Mediterranean)

Bárbara¹,

Cabello²,

Bouché³

et al. 2019

Preprint

View full text Add to dashboard Cite

Abstract. Structural uncertainty is a key parameter affecting the accuracy of the information contained in static and dynamic reservoir models. However, quantifying and assessing its real impact on reservoir property distribution, in-place volume estimates and dynamic simulation has always been a challenge. Due to the limitation of the existing workflows and time constraints, the exploration of all potential geological configurations matching the interpreted data has been limited to a small number of scenarios, making the future field-development decisions uncertain. We present a case study in the Lubina and Montanazo mature oil fields (Western Mediterranean) in which the structural uncertainty in the seismic interpretation of faults and horizons has been captured using modern reservoir modeling workflows. We model the fault and horizon uncertainty by means of two workflows, the manually interpreted and the constant uncertainty cases. In the manually interpreted case, the zones of ambiguity in the position of horizons and faults are defined as locally varying envelopes around the best interpretation, whose dimensions vary according to the diffractions and amplitudes of the seismic data throughout the surface interpretation. In the constant case, the envelope dimensions are kept constant for each horizon and each fault. Both faults and horizons are simulated within their respective uncertainty envelopes as provided to the user. In all simulations, conditioning to available well data is ensured. Stochastic simulation was used to obtain 200 realizations for each uncertainty modeling workflow. The realizations were compared in terms of gross rock volumes above the oil-water contact considering three scenarios in the depths of the contact. The results show that capturing the structural uncertainty in the picking of horizons and faults in seismic data has a relevant impact on the volume estimation. The models predict percentage differences in the mean gross rock volume with respect to best estimate interpretation up to 16 % higher and 22 % lower. The manually interpreted uncertainty workflow reports narrower gross rock volume predictions and more consistent results from the simulated structural models than the constant case. This work has also revealed that, for the Lubina and Montanazo fields, the fault uncertainty associated with the major faults that bound laterally the reservoir strongly affect the GRV predicted. The multiple realizations obtained are geologically consistent with the available data and their differences in geometry and dimensions of the reservoir allows us to improve the understanding of the reservoir structure. The uncertainty modeling workflows applied are easy to design and allow to update the models when required. This work demonstrates that knowledge of the data and the sources of uncertainty is important to set up the workflows correctly. Further studies can combine other sources of uncertainty in the modeling process to improve the risk assessment.

show abstract

Added Value by Fast and Robust Conditioning of Structural Surfaces to Horizontal Wells for Real-World Reservoir Models

Cited by 6 publications

References 10 publications

A Novel Method for Locally Updating an Earth Model While Geosteering

A Novel Method for Locally Updating an Earth Model While Geosteering

Quantifying the impact of the structural uncertainty on the gross rock volume in the Lubina and Montanazo oil fields (Western Mediterranean)

Quantifying the impact of the structural uncertainty on the gross rock volume in the Lubina and Montanazo oil fields (Western Mediterranean)

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