This paper describes a new method for water control by the use of bullhead injection. A water based gelant is emulsified in oil and injected into the formation. The emulsion is designed to separate into a water phase and an oil phase at static conditions in the formation. Upon reaction in the formation the water phase gels up while the oil phase remains mobile. It has been found that the controlling parameter for disproportionate permeability reduction (DPR) is to control the fraction of gel occupying the porous media. The water fraction in the emulsion controls the reduction in relative oil and water permeabilities. A program was undertaken to verify this DPR method in a field test, using a commercial blocking gel system. The first treatment was performed in well 30/3 A 16 T2 at the Statoil operated Veslefrikk field offshore Norway. Results show that water production was reduced by 30% after the pilot test, while maintaining the oil rate. As expected, total well productivity was reduced by more than 80%. The treatment consisted of 124 m3 emulsion, bullheaded from surface. Step rate testing and ion water analysis were combined to study the relative change in flow contribution between the 6 perforated intervals. Introduction The increasing number of high water-cut producing wells requires simple and cost effective water control technologies. One option is bullhead injection of chemicals capable of reducing the water permeability more than the oil permeability, normally described as Disproportionate Permeability Reduction (DPR) or Relative Permeability Modification (RPM). DPR will be effective in multilayered reservoirs without crossflow and with some zones producing clean oil or in treating coning problems.[1–3] In such situations DPR treatment will reduce the water cut and may result in increased oil production. The existence of DPR fluids is well known.[4–8] DPR fluids may be classified as polymer systems, weakly crosslinked gel systems or rigid gel systems. The polymer systems are the most frequently used. The DPR mechanism has been explained by polymer adsorption on a water-wet rock surface.[9,10] This will reduce the effective pore space for flowing water. The ratio between the thickness of the adsorbed layer, e, and the pore radius, r, is used to express the permeability reduction, RRF (defined as the ratio between permeability before and after treatment), using Poiseuille flow in a bundle of capillary tubes. ………………………………………..(1) The oil will flow more or less un-restricted in the middle of the pores. Consequently the oil permeability reduction, RRFo, will be lower than the water permeability reduction, RRFw. From Eq. 1 the following can easily be derived:RRF will decrease with increasing pore radius, i.e. increasing the permeability.RRF will increase by increasing the thickness of the adsorbed layer. The latter one can be obtained by using polymers with larger molecular weight and higher affinity for adsorption. Alternatively weak gels or aggregates can be formed in-situ by injection of polymer and crosslinker.[5,11–12] Often, the polymer and the weakly crosslinked gel systems involve additional retention mechanisms, such as pore trapping. The use of preformed gel particles will also increase the effective adsorption thickness.[13] Rigid crosslinked gel is normally used for total blocking. Blocking gels have DPR properties[7,14–17] but for practical purposes in matrix treatment the oil permeability reduction has been recognized far too high for bullheading. However, crosslinked gels could be promising alternatives if the permeability reduction, RRF, can be controlled. This is mainly because crosslinked gels show (i) better temperature stability, (ii) DPR properties regardless of wettability and (iii) high RRF also in high permeability zones. A crosslinked gel will probably also be more resistant towards the high shear rates close to the wellbore. Consequently the volume of active DPR fluid can be reduced. It has been demonstrated that RRF depends on the fraction of gel occupying the pore space.[15–16,18]
Presently wells are drilled in the North Sea approaching a horizontal reach of 8 km. Plans for the near future is to extend these towards and beyond 12 km. Well friction is one of the most important limiting factors in this process. Torque and drag prognosis are today developed on in-house simulators. Although a good tool for planning, improvements are made on an trial and error basis, and, these simulators have limited availability. To provide more insight into the frictional aspect, a larger study was undertaken. Explicit analytical equations are derived to model drill string tension for hoisting or lowering of the drill string. The equations are developed for straight sections, build-up sections, drop-off sections and side bends. Both constant curvature models and a new modified catenary model are derived. The new catenary model is developed for arbitrary entry and exit inclinations. Equations to determine well friction in fully 3-dimensional well profiles are also given. Furthermore, based on the tension equations, expressions for torque and drag are developed. Equations for combined motion and drilling with motor are also given. Using these equations, the total friction in a well is given by the sum of the contributions from each hole section. A field study offshore Norway is included in the paper. Using the equations derived in the paper, the well path is chosen to minimize the torque on the rig, which is the limiting factor. The paper also summarize a number of guidelines for extended-reach well design, and shows the design of an ultra- reach well of more than 12 km reach. P. 819
A fundamental premise underlying the industry's focus on integrated operations (IO or 'i-field/e-field/smartfield') is that IO will improve decision making. Improved decisions should in turn lead to safer and more efficient operations. IO characteristics that are associated with better decision making include: Increased use of real time data, more multi-disciplinary teamwork, more work performed independent of physical location, and more work performed in a parallel as opposed to a serial work mode. However, IO introduces potential threats to high quality decision making as well. These threats include: A sceptical workforce resisting change, group based and distributed decision making that blurs lines of command, information overload, reduced understanding of local (i.e. installation specific) factors as decision makers are removed from the drilling and production facilities, and heightened complexity and interactivity can make it difficult for decision makers to maintain overview during an incident. The present paper describes how potential drawbacks of IO were met when IO was implemented on major oil fields in the North Sea. Emphasis was placed on end user involvement in the implementation of IO, development of training and information material focusing on new ways of working, human centred design of operation rooms and ICT, and controlled changes in relevant work processes. The main conclusion that can be drawn this case study is the need to balance changes in technology with corresponding changes in people and organisation. Efforts to maintain, or create a new, equilibrium between people, technology and organisation are fundamental in achieving IO's goal: Better decisions. A myopic focus on technology, on the other hand, may result in resistance to change in the organisation, and the true potential of IO will not be realised. Introduction Studies on decision making in the oil and gas industry have shown that decision making processes regularly deviates from ideal or prescriptive models of decision making, and that outcomes frequently are suboptimal from a cost-benefit perspective (1, 2). Faulty decision making seems to flourish both in a major field development context and in a day-to-day operational context. A number of factors can explain why high quality decision making is difficult in the industry. It is well known that cognitive biases have a strong influence on decision making (3), and the uncertainties associated with models, data and tools used by the industry (e.g. reservoir models) may give these biases a particularly powerful impact. Furthermore, in a volatile market with exploration and production in increasingly remote and politically unstable regions, the best strategic options are often clearly identifiable only in hindsight. However, means to improve decision making may not be too far away. Today the oil and gas industry is undergoing a transition made possible by new and powerful information technology. Traditional work processes and organisational structures are challenged by more efficient and integrated approaches to exploration and production. The new approaches may reduce the impact of traditional obstacles - whether they are geographical, organisational or professional - to efficient decision making (4, 5). Descriptions of the new approaches exist elsewhere (e.g. 15), and will not be repeated here. The approaches can be subsumed under the heading Integrated Operations (IO). Numerous definitions of IO exist in the industry. In (6) IO is defined as: New work processes which use real time data to improve the collaboration between disciplines, organisations, companies and locations to achieve safer, better and faster decisions. In this definition improved decision making is highlighted as the main goal of IO. It is assumed that improved decision making processes in turn will lead to increased production, less downtime, fewer irregularities, a reduced number of HSE-related incidents, and in general a more efficient and stream-lined operation.
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