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Multilateral Well Performance Prediction

Authors: J.R. Salas; P.J. Clifford; D.P. Jenkins;

Multilateral Well Performance Prediction

Abstract

Abstract Potential reservoir applications of multilateral wells are identified. Methods for calculating their productivity and performance are described. These methods are used to show how productivity depends on wellbore geometry and reservoir properties. Also, the performance of multilateral wells is compared with horizontal wells in reservoirs with 2-phase gravity drainage, and multilateral wells are shown to be an effective solution to the waterflooding of a faulted reservoir. Introduction The drilling and completion of multilateral wells is a major emerging technology within the oil industry1. Some reservoir applications of the technology have been discussed, and the need to identify and quantify the reservoir benefits of multilateral wells has received attention. The emphasis in this paper is on identifying reservoir target types for multilateral wells, and extending our current analytic and numeric modeling techniques in order to meet the challenge of predicting multilateral well performance in such targets. Comparison is made particularly between multilateral and horizontal well performance since, in many cases, the horizontal well will be either the competing technology, or the basis for a multilateral sidetrack. 2. Potential Multilateral Well Applications The first stage in predicting the performance of multilateral wells is identifying the types of reservoir application for which they may be used. One important factor is that, in addition to new wells, multilaterals may be drilled from existing wells and can benefit existing reservoirs. Some of the main potential applications of multilateral wells have been identified by a multidisciplinary team. They are grouped into 8 categories in Table 1, recognizing that any individual well may fall within more than one category. Not all of these applications are achievable with current technology, but the industry is working on tools to provide new options for multilaterals. Some of the applications (e.g. no. 1), while breaking new ground in drilling and completion technology, do not require new methods of performance prediction, since the multilateral branches are essentially non-interfering. Other applications (e.g. no. 6) are highly case-specific. The examples considered in this paper are concerned with well productivity, and with gas/water production, in multilateral wells with interference between branches, and fall mainly within applications 5 and 7. 3. Performance Prediction Techniques To account for interference between multilateral branches, it has been necessary to develop new analytic techniques, and to extend current numeric modelling techniques. 3.1 Analytic Methods. An analytic model was developed to give a rapid assessment of the productivity of different multilateral well configurations. The model, whose formulation is described in the Appendix, calculates the total skin factor of a multilateral well in a homogeneous, infinite slab, single-phase reservoir, for very general wellbore geometry. Extensions of the model allow isolated branches and wellbore friction to be included. Examples of the use of this model are given in Section 4. Although the model cannot always be directly applied to multi-phase well performance, it has been successfully used to validate and develop grid-block connection factors for multi-phase simulation models. In addition, if used properly, it can give good ballpark estimates for use in initial well planning and completion optimization. 3.2 Numeric Methods and Validation. Calculating the benefits of multilateral wells in heterogeneous reservoirs with multi-phase flow, where issues such as gas and water coning are of major importance, requires full numeric simulation. Multilateral wells must be represented using a set of grid-block well index factors WI of the form: P. 591

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
33
Top 10%
Top 10%
Top 10%
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