The impact of a quick 4D seismic survey and processing over the Halfdan Field, Danish North Sea

Calvert, M.; Roende, H.; Herbert, I.; Za, J.; Hickman, Peter; Micksch, U.

doi:10.3997/1365-2397.2014003

Cited by 7 publications

(3 citation statements)

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“…c. The gas may be present at expected locations, for example at local structural highs. d. As we are aware that amplitude decrease (softening) in the 4D seismic data is a consequence of gas, as well as pressure increase (Calvert et al, 2014), the amplitude decrease caused by an increase in pressure around a water injection well is removed from the analysis; however in the case of a gas injector well (where an increase in pressure and the presence of gas cause the same softening effect on seismic), the magnitude of the pressure and gas saturation will need to be determined in order to ascertain which has a more dominant effect on the seismic. To perform the history match, an initial ensemble of models is created using the Latin Hypercube Experimental Design (LHED) method (Roggero et al, 2007), as multiple models have extensive coverage of the search space and deliver robust results.…”

Section: Methodsmentioning

confidence: 97%

Seismic Assisted History Matching Using Binary Image Matching

Obidegwu¹,

Chassagne²,

MacBeth³

2015

Europec 2015

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This paper presents a history matching scheme that has been applied to production data and time lapse seismic data. The production data objective function is calculated using the conventional least squares method between the historical production data and simulation predictions, while the seismic objective function uses the Hamming distance between two binary images of the gas distribution (presence of gas (1) or absence of gas (0)) sequenced over the different acquisition times. The technique is applied to a UKCS (United Kingdom Continental Shelf) field that has deep-water tertiary turbidite sands and multiple stacked reservoirs defining some degree of compartmentalisation. Thirty five parameters are perturbed in this history match, they can be classified as volumetric parameters (net-to-gross, pore volume), transmissibility parameters (permeability, transmissibility), and end points of the relative permeability curves (critical saturation points). An initial ensemble of fluid flow simulation models is created where the full range of uncertain parameters are acknowledged using experimental design methods, and an evolutionary algorithm is used for optimization in the history matching process. It is found that permeability and critical gas saturation are key parameters for achieving a good history match, and that the volumetric parameters are not significant for this match in this particular reservoir. We also observe that matching only to production data marginally improves the seismic match, whilst matching to only seismic data improves the fit to production data. Combining both sets of data delivers an improvement for the production data and seismic data, as well as an overall reduction in the uncertainties. A unique feature of this technique is the use of the Hamming distance metric for seismic data history matching analysis, as this circumvents the use of the uncertain petroelastic model. This approach is easy to implement, and also helps achieve an effective global history match.

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Section: Methodsmentioning

confidence: 97%

Seismic Assisted History Matching Using Binary Image Matching

Obidegwu¹,

Chassagne²,

MacBeth³

2015

Europec 2015

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“…The field is developed in an alternating pattern of km-long multistage horizontal producer and water injector wells aimed at maximum water sweep efficiency by applying the Fracture Aligned Sweep Technology (FAST) concept, developed by Maersk Oil (Lafond et al 2010). Several first moves with respect to technology implementation have been made for the field with respect to optimisation (Calvert et al 2014(Calvert et al , 2016Wherity et al 2014). The key for success in these studies has been to link well data representing performance over many km and stimulation zones with seismic data revealing the spatial geometry.…”

Section: The Halfdan Fieldmentioning

confidence: 99%

“…The key for success for the operation of the Halfdan field has been to link well data representing performance over many km and stimulation zones with seismic data that gives the spatial geometry (c.f. Calvert et al 2014Calvert et al , 2016.…”

Section: Water Types and Oil Production Driversmentioning

confidence: 99%

Oil production monitoring and optimization from produced water analytics; a case study from the Halfdan chalk oil field, Danish North Sea

et al. 2018

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Produced water analysis is a direct source of information to the subsurface processes active in an oil field. The information is, however, complex and requires a multidisciplinary approach and access to multiple data types and sources to successfully unlock and decode the processes. We apply data analytics on a combined data set of water chemistry and oil and gas production data measured in the production stream from five wells in the Halfdan field. The field is produced applying extensive water injection to ensure the most efficient water sweep of the reservoir. Relationships between daily production data and water chemistry are examined with Principal Component Analysis (PCA), and systematics with respect to predictability of daily changes in the oil production from water chemistry are examined with partial least square (PLS) regression models. For each well, the water chemistry provides a high degree of predictability with respect to daily oil cut in the production stream. The results have potential for application within prediction of sweep efficiency, bypassed oil and for prediction of water breakthrough. Full potential, however, depend on successful implementation of water chemistry-oil production analytics into other data domains such as seismic (4D) data and well work-over data.

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Introduction to the Oil Industry and Oil Show Evaluation: A Personal Retrospective

Dolson

2016

Understanding Oil and Gas Shows and Seals in the Search for Hydrocarbons

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The impact of a quick 4D seismic survey and processing over the Halfdan Field, Danish North Sea

Cited by 7 publications

References 0 publications

Seismic Assisted History Matching Using Binary Image Matching

Seismic Assisted History Matching Using Binary Image Matching

Oil production monitoring and optimization from produced water analytics; a case study from the Halfdan chalk oil field, Danish North Sea

Introduction to the Oil Industry and Oil Show Evaluation: A Personal Retrospective

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