Surveillance—Maintaining the Field from Cradle to Grave

Grose, Trevor

doi:10.2118/108498-ms

Cited by 4 publications

(1 citation statement)

References 1 publication

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“…The challenge was to supplement the existing data to address the key waterflood risks to enable the waterflood to be optimised. A surveillance planning process was undertaken, in line with that used on other BP fields and described in reference [3]. Having identified the main risks and uncertainties associated with waterflood, the different data types and monitoring technologies available to address these were evaluated.…”

Section: Surveillance Planningmentioning

confidence: 99%

Waterflood Performance in a Depleted Fractured Chalk Reservoir

Griffin

Best

Thingvoll

et al. 2007

SPE Offshore Europe Oil and Gas Conference and Exhibition

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fax 01-972-952-9435. AbstractValhall is a fractured chalk reservoir in the Norwegian sector of the North Sea which has been producing under compaction and solution gas drive since 1982. A water injection pilot led to sanctioning of the Valhall Waterflood Project which began injection in the crest of the field early in 2006. The predictions of Valhall waterflood performance covered a wide range of parameters that included fault and fracture pattern, water chemistry, compaction due to depletion and water weakening, 3 phase relative permeabilities, scaling and souring that all will impact sweep, recovery and well integrity.To gather the key data required to make decisions in waterflood planning in the correct time frame, a comprehensive surveillance plan was drawn up. This included open and cased hole logging data, a dedicated monitoring well, time lapsed seismic and injection / production well performance data. This data is also used to manage short term waterflood issues associated with potential water breakthrough, monitoring pressures and managing the water chemistry.Early data has revealed variability in the waterflood response in the crest. Two types of responses have been observed, a fractured zone and a more matrix dominated zone. Understanding these variations is key for placement of future injectors and for the expansion and optimization of the Valhall Waterflood Project.

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Section: Surveillance Planningmentioning

confidence: 99%

Waterflood Performance in a Depleted Fractured Chalk Reservoir

Griffin

Best

Thingvoll

et al. 2007

SPE Offshore Europe Oil and Gas Conference and Exhibition

View full text Add to dashboard Cite

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Assisted History Matching as a useful tool: An example from Trinidad

Walker¹,

Kromah²,

Pham³

et al. 2008

SPE Indian Oil and Gas Technical Conference and Exhibition

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The goal of all history matching for the reservoir models is to generate accurate predictions. There is also an assumption that a better history match should lead to a more accurate prediction, which can lead an asset team to concentrate on a single model. The assisted history match techniques allow us to generate multiple models that satisfy the surveillance 1, and understand a range of outcomes for a set of models. What we need is to provide assurance that we are searching correctly for the range in outcomes, to understand the interaction between uncertainty, surveillance, and the business decision. This paper describes an example for the Mahogany field in Trinidad, which is mainly gas with a thin oil rim. As the reservoir pressure is decreasing, there is a window of opportunity to drill an additional well. The first task is to determine the correct value of a new gas well, to protect against water encroachment. The Mahogany field used BP's Top Down Reservoir Modeling (TDRMTM) to test a hypothesis - is it possible to find models that match history, and have certain key features in the future? In this case we are specifically looking for a scenario with water at the existing gas well locations. Since the system is generating discrete models, we can then test which new gas well locations would mitigate the water. We've also been able to use an idea from our Alaskan operations, and consider water injection with a dump flood. The appraisal of the water injection has been performed using computer assisted depletion planning tools (TDDPTM 2) to assess the best location and strategy for such a well. Background The key task for a reservoir simulation is providing an accurate estimate of future performance for existing and planned wells. Unfortunately, the reservoir model will always be coarser than reality due to simulation constraints, and contain approximations in the geology due to observational limitations. As a general rule, the only thing that can be said of a single model is that it will be wrong in some detail, and the use of a single model requires the subsurface team to know whether the errors are significant and whether there will be a surprise in the future. With the development of multiple models, we can test what other reservoir descriptions also satisfy the observational constraints 4. If the range of alternatives has been set up correctly, then we should be able to determine the probability of certain outcomes, and alter our depletion plan to test whether the reservoir description is possible, and what our best strategy should be in that case. We shall use the framework provided by an assisted history matching tool to test discrete alternative cases.

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Combining a Surveillance Testing Workflow into the Assisted History Matching Process to Reduce Uncertainties in a SAGD Reservoir

2013

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Assisted History Matching (AHM) is a technology that enables reservoir engineers to: automatically create multiple realizations by combining different choices of the reservoir parameters (uncertainties); run the simulation jobs (experiments); analyze the results to determine an objective function such as history match quality for each realization; and then set up new simulation jobs by using an optimizer to determine the parameters combinations. The history-matched models can then be used in optimization on a production process for the purpose of optimizing several depletion development plans through the Closed-Loop Reservoir Management (CLRM) workflow. The system is able to update the models as field measurements become available, and the reservoir management can be changed from periodic to a near-continuous process. The CLRM has become popular in fields where modern sensors can bring huge quantity of real-time information. In this paper, a workflow has been developed to test if the existing field surveillance or/and new surveillance add value to the AHM process. To do this, a single deterministic reservoir description was designated as the truth case, and using an exploitative optimizer a range of equivalent history matched models were generated and tested for fidelity to the truth case. Two different formulations of the objective function were created, the primary containing only rate measurements in well pairs and a second that further included temperature measurements in observation wells to see how these additional observations would alter the quality of the prediction. An additional set of observations for future temperature observations in the six months after the end of the history match were created, again to test how such observations reduced the uncertainty range of the reservoir in future outcomes. We are also testing if there is a difference between observation well locations, and where an ideal observation well could be located to find the clearest signal indicating future performance. The reservoir model is that of a 3D Steam Assisted Gravity Drainage (SAGD) thermal reservoir. Two horizontal well pairs provide steam and allow production, and ten vertical observation wells are distributed throughout the SAGD reservoir with five stations along each well for pressure and temperature measurements. The results showed that the temperature measurement in five observation wells failed to reduce the uncertainty range in the cumulative field oil production and also failed to exclude models that have the dangerous characteristic of being a good history match yet a poor prediction. The uncertainty in the future reservoir outcomes can be reduced by 72 % when the temperature measurements in ten observation wells were used in the AHM process for a period of six months following the first year and a half production, potentially indicating when a key signature becomes observable. These observations were completed in different areas throughout the reservoir and had captured the development of the steam chamber with...

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Surveillance—Maintaining the Field from Cradle to Grave

Cited by 4 publications

References 1 publication

Waterflood Performance in a Depleted Fractured Chalk Reservoir

Waterflood Performance in a Depleted Fractured Chalk Reservoir

Assisted History Matching as a useful tool: An example from Trinidad

Combining a Surveillance Testing Workflow into the Assisted History Matching Process to Reduce Uncertainties in a SAGD Reservoir

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