Connected Volume Calibration for Well-Path Ranking

Gutteridge, P.A.; Gawith, D.E.

doi:10.2523/35503-ms

Proceedings of European 3-D Reservoir Modelling Conference 1996

DOI: 10.2523/35503-ms

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Connected Volume Calibration for Well-Path Ranking

P.A. Gutteridge¹,

D.E. Gawith²

Abstract: Ccpyrght199S S=)etyd Pefrokum Englneem ThIsp er waspr~ared lorpresentatlon atthe EurWean 3Dmsewo,r wdelitng conference % hddm tavanyer Norway 16-17 Aixd 1996 Thm paper was selecfed for presentation by the SPE programm conmuftee Iollow!ng revmu of mlormatmn contatned In an abstract s.bmmed by the authors Contents of the paper ap rrnented have not b6enrev,ewed by[he Smmtyof Petroleum Engineers andaresubject!o correctlonby fheauihors The matenalaspresentec dcms nd necrnsanlyrelbct anyposdmn ofihe Socmtyof Petrole… Show more

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Reservoir Opportunity Index - Advance in Well and Subsurface Design for Cost Effective Field Development

Ataei

Soni

Chuah

et al. 2014

SPE Asia Pacific Oil &Amp; Gas Conference and Exhibition

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Phase development is key to any successful field development in complex and compartmentalized reservoirs. The balance of cost, value and risk drives the oil companies to learn from well and reservoir data as they develop the field. Naturally, well productivity will enhance in each phases, by a better well and completion design while the remaining mobile oil, hydrocarbon saturation and reservoir pressure are diminishing. Subsurface target selection and ultimately well design needs to be optimized rigorously in order to meet the expected value of each well in every drilling campaign. This paper gives a new insight in Reservoir Opportunity Index (ROI) or Simulation Opportunity Index (SOI) which combines the key elements of each target (Flow Capacity, Remaining mobile oil and pressure) into a normalized parameter. There are several papers1,2,3 which introduce the application of this method in several case studies. All of those works is guided by existing simulation model which is history matched until present time. The model is then used to generate the SOI map with the MAX (SOI) function will be treated as the optimize location for future well location. We had tested this method in several case studies and have found that more detail analysis in SOI indexes are needed before accepting the results of the MAX (SOI) function. Having several infill drilling campaign in the past gives us an opportunity to evaluate the SOI based on the previous data and production performance. Correction of the mathematical function may be needed to better match the historical data which is not limited to production only but the Productivity Index (PI), pressure and remaining oil map. The method have been applied in several cases including a tight gas reservoir and two vast multiple stacked oil reservoirs with reliable full field model. It will be shown in this paper that this method gives a more reliable targets in subsurface and well design and hence introduced as an integrated part of well optimization workflow. Like other methods, it should be used with care as there are limitations in each case. This paper highlights those limitations that have been observed in our work and advised how to overcome the limitations.

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Reservoir Opportunity Index - Advance in Well and Subsurface Design for Cost Effective Field Development

Ataei

Soni

Chuah

et al. 2014

SPE Asia Pacific Oil &Amp; Gas Conference and Exhibition

View full text Add to dashboard Cite

show abstract

Infill Well Portfolio Management under Uncertainty – Application to the 8 TH Reservoir, Austria

Sieberer

Peisker

Clemens

et al. 2017

SPE Europec Featured at 79th EAGE Conference and Exhibition

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The risk of economic failure of infill drilling campaigns increases with the increasing maturity of an oil field. The increased risk is due to the lower remaining movable oil in the late stages of a field's life compared to earlier phases. Despite the additional information owing to drilling of wells and production history, substantial geological and dynamic uncertainties remain. In this paper, an approach is presented for selecting an infill well portfolio of 10 wells from a total of 96 that explicitly accounts for these uncertainties. The geological uncertainty can be exposed by generating a multitude of geological models conditioned to known log/correlation data. These models need to be classified and a subset of representative models extracted that in turn are calibrated (history matched) to past field performance and then used for forecasting. Calibration using a suitable ensemble of representative geological models aims to maintain geological diversity while reducing the error to historical data through an objective function. Probabilistic Property Maps can then be generated to identify potential infill well locations. Probabilistic maps offer a major improvement compared to selection of infill well locations using a single geological realization. For mature assets, forecasting requires simulation of incremental oil recovery since infill wells represent incremental projects over a base case. Using an appropriate ensemble of models allows probabilistic representation of the incremental oil production and associated economics. First, individual infill well performances are forecasted. Next, the individual infill well locations are evaluated taking the history matching error into account and using utility theory to cover the risk adverseness attitude of the company. Doing so enables selection of an infill well portfolio under uncertainty and leads to a selection of well locations carrying lower risk compared to a selection of locations neglecting history match error and/or disregarding the risk attitude of a company.

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Connected Volume Calibration for Well-Path Ranking

Cited by 2 publications

References 1 publication

Reservoir Opportunity Index - Advance in Well and Subsurface Design for Cost Effective Field Development

Reservoir Opportunity Index - Advance in Well and Subsurface Design for Cost Effective Field Development

Infill Well Portfolio Management under Uncertainty – Application to the 8 TH Reservoir, Austria

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