TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractThis paper discusses the application of an optimisation technique to manage a field consisting of wells with Intelligent Well Technology (IWT) completions that allow the operator to reconfigure well architecture without well intervention. There is currently no generally accepted, efficient, optimisation technique available to optimise the IWT operation so as to maximise well production. The Sequential Quadratic Programming (SQP) candidate technique has previously proved its value in small and large-scale optimisation problems involving large-scale (gas-lifted) well production networks. SQP's ability to solve this new nonlinear problem in a relatively reasonable time will be explained in this paper.In the previous publications 1-4 we used a reservoir simulator controlled by a manual optimisation procedure to develop a value-statement for IWT. This method has proved it could increase value during the plateau period, but efficient optimisation of the decline period was too demanding in terms of engineering time & computer power. This later requires an automatic optimisation tool to be cost effective.The Reservoir simulator has been linked to a (SQP based) Network optimiser so as to set the well and zone so that the production objectives are maximized, subject to the normal constraints (e.g. pressures, flow rates, water cuts etc. frequently imposed on the individual zonal or well production).The cumulative production increase achieved with manual optimisation (compared to the field level control) was doubled once automatic optimisation with zone-level control was implemented for the real-field based example studied previously. Automatic optimisation did significantly improve tail-end production, but delivered its greatest value by extending the plateau period.The results show that the use of automatic optimisation is valuable when building a "value statement" for the implementation of IWT within a particular field. Automatic Production optimisation (using conventional well) in reservoir simulationProduction and Injection wells are usually connected together by a surface network contain pipes, chokes, pumps, etc. A number of studies have been performed in order to set the flow rate per well or per group of wells, different tools have been used to meet constraints inherent to this network of these facilities. Reservoir modellers may optimise rate allocation to optimally determine well rate setting so that network objectives and constraints are simultaneously satisfied.Literature examples previously reported in this area include:1. Davidson and Beckner 5 used SQP to set well rates in a facility network of a reservoir simulator. SQP was used to meet the objectives of maximizing the oil production subject to constraints on pressures, flow rates and stream compositions. The approach was tested on black oil and compositional examples. The examples show how the method has been formulated, individual well rates set and how infeasible conditions can be handled.2. Lo et al. 6 ...

The Application of Intelligent (or Smart) Well Completion Technology (IWT) has not progressed as rapidly as originally expected. This is partly due to management's lack of confidence that the "added value" is sufficient to justify the extra investment. This concern can be addressed by publication of well-documented examples of IWT delivering value. This paper describes the detrmination of the "added IWT value" from maximising oil production, within allowable gas constraints, for the Norwegian NH-field that produces from a thin oil-rim using high productivity, horizontal-wells. The well drawdown is similar, or lower, than the frictional pressure drop along the completion length. This generates a skewed production profile along the length of the completion; the bulk of the oil production - and early gas and water break-through - occurring at the heel of the well. This is further accentuated by the presence of a tilted, high-permeability sand that connects the heel of the well to the gas cap. A further complication is that the bubble point is close to the initial reservoir pressure (in fact at the gas-oil-contact, the saturation pressure and the reservoir pressure are identical) and 34% of the total Hydrocarbon Liquid is associated condensate in the gas cap. This paper not only shows how the "added IWT value" was derived, but also the:Development of a well-performance management philosophy,Optimisation of the conventional well using a sector of the full-field model,Insertion of a detailed, Intelligent Well (I-well) completion model within this model, (iv) Development of an I-well design and operation philosophy,Illustration of the advantages, disadvantages and utility for well optimisation of available keywords within commercial simulation packages. Finally, understanding how the I-well Completion "adds value" allows the development of guidelines for the choice of candidate wells in this type of reservoir where IWT is capable of delivering value. Introduction I-well completions employ localized pressure restrictions (Interval Control Valves (ICVs)) to balance the production profile along the length of the well completion by splitting it into two (or more) sections. The aim of I-wells is to optimise the production (maximizing net oil while delaying the gas and water breakthrough)[1]. This can either be done:at a well or multi-well system level in order to maximize the instantaneous oil production by managing the available well production potential if it is greater than the production system capacity, orin a reactive manner (responding to the breakthrough of unwanted water or gas) at the wellbore, orby optimizing the (complex) reservoir/well system through control of the flood fronts between the wells by managing the injection and off-take profile in an active manner. This latter requires sensors that can image fluid fronts between the wells. Alternatively a model capable of predicting the flow of fluids within the well and reservoir with time could be used. A detailed well model incorporated within a reservoir simulation model is the most complete (and complex) option for this. Still, an optimisation methodology is required to maximize the production and take advantage of the flexibility offered by the ICV's.

Reservoir compaction in deep water, unconsolidated, turbidite reservoirs can cause large-scale permeability damage to near-wellbore area, the resulting skin reducing the well productivity. This is due to the depleting reservoir pressure resulting on an increased effective stress on the fabric of the reservoir rock leading to a reduction in both permeability and porosity. Permeability reduction will decrease recovery while porosity reduction will improve recovery by maintaining the fluid pressure & increasing the oil saturation. The interplay of these phenomena was studied using a reservoir simulation model of a typical deepwater, compacting, compartmentalized layered reservoir. Eighteen months production experience was available for history matching. This paper will show how the above understanding can be used to optimize the well performance and explain "unusual" production performance observations e.g. a decreased water cut was predicted if water injection was implemented. This study reviews the potential value creation through development of a compacting reservoirs using Intelligent Well Technology (IWT) compared to a conventional well development. IWT offers great flexibility to monitor, operate and control production at the Zone and Reservoir level. This led us to examine whether the draw down around the wellbore could be optimized so that permeability damage is minimized as a means of increasing recovery in compacting reservoirs. This paper shows how evaluation of I-well value generation has to combine the traditional reservoir engineering studies of well location and pressure maintenance while simultaneously optimizing the details of the well completion design and the newer technologies associated with managing compacting reservoirs. A doubling of the field reserves was predicted by completing the new well with IWT. IWT also effectively managed non-optimum situations e.g. placement of the well in the incorrect location. Introduction The CT Field is located approximately 170 miles south-southwest of New Orleans some 2,100 feet of water (Figure 1). One of the major concerns facing the CT development team that the production was planned from two, separate, unconsolidated sands. IWT is thought to be the tool that can help to solve some of the resulting challenges. The high cost of I-well developments makes it essential that the reservoir behavior is sufficiently well understood that a confident value-proposition can be made before making the decision to install such technology in the field. The potential benefits from IWT for a two reservoir sand system has frequently been discussed[1–5]. In these field applications improved production performance was achieved from commingled completion zones (or reservoirs) with very different properties or when different fluids are being produced. The new factor introduced in this study is the high level of reservoir rock deformation occurring due to formation pressure depletion during oil production.

TX 75083-3836, U.S.A., fax +1-972-952-9435. AbstractIn-situ reservoir stress measurements are essential input to a wide variety of the production and injection applications of reservoirs. Most of the reservoirs in this article require water injection to maximize recovery without breaking the matrices unintentionally. In some cases, it is also important to create a controlled fracture growth in a formation unit without breaking bordering barriers or zones. The main purpose of the in-situ reservoir stress testing of the case studies in this article is to calculate the minimum stress to improve the reservoir management plans for well placement, production, injection and fracturing processes.One approach of measuring stresses in many zones is to use the wireline conveyed stress testing tools. The wireline conveyed in-situ reservoir stress testing measurements are frequently performed in the Sultanate of Oman for a wide range of operational and geomechanics applications such as but not limited to:• Hydraulic fracturing • Fracture growth/containment issues • Polymer injection • Borehole stability • Sand production prediction • Stress evolution with depletion, hot and cold injectionThe stress testing zones vary from tight to high permeable zones as well as shale zones. The complexity and wide variety of the stress testing applications inevitably led modifications and improvements on the wireline conveyed stress testing tools. These improvements mainly are various types of pumps, higher performance dual packers and mandrels, innovative stress testing methods. The latest improvements and methods in stress testing help addressing the broader range of formations (deep and shallow, tight and permeable) in an extensive type of wells from vertical or deviated to horizontal.In this article, the examples of several unique stress testing applications are presented. Shale stress testing with a viscous fluid, horizontal well stress testing, tight and very high permeability formation stress testing, sleeve fracturing stress testing methods are discussed in details.

TX 75083-3836 U.S.A., fax 01-972-952-9435. AbstractThe main challenge facing the oil industry is to reduce development costs while accelerating recovery while maximising reserves. One of the key enabling technologies in this area is intelligent well completions. Downhole inflow control devices allow for the flexible operation of non-conventional wells. By placing sensors and control valves at the reservoir face, engineers can monitor reservoir and well performance in real time, analyse data, make decisions and modify the completion without physical intervention to optimise reservoir and asset performance.