Drilling through depleted sands can result in a multitude of problems such as lost returns, differential sticking, difficult logging and/or not being able to reach the target depth. Often curing lost circulation can be difficult and costly as a result of associated nonproductive time and escalating mud costs. Remedies such as cement plugs, squeezes, expandable liner and casing while drilling can be costly solutions. The use of fluid management techniques, team efforts and proper engineering have lead to the development of an innovative approach to prevent problems and avoid the complex processes of curing mud losses and freeing stuck pipe. This new preventative approach with water-based mud has been applied in several fields, while drilling through a series of highly depleted sands and has proven to be very effective in preventing differential sticking and mud losses. Although operationally successful, the geomechanics and the fluid design resulting in these successes are not well understood. A geomechanical analysis indicates that two mechanisms might contribute to the success:The near wellbore region is turned into a non-porous rock because the particles in the new mud tend to block the pore spaces. The theory of poroelasticity indicates that fracturing pressure is increased by reducing the difference between mud pressure and the pore pressure immediately behind the borehole, which for non-porous rock is zero.Because of this blockage, it is possible that the near wellbore rock strength is increased. This strengthening effect decreases tangential stress and increases fracturing pressure. The geomechanics model can be used to define the operational limits of various mud weights with proper drilling fluids design. This model would enable a consistent and focused approach on drilling fluid design to effectively mitigate massive fluid losses associated with drilling through severely depleted sands or in narrow pore pressure/fracture gradient environments. Introduction Lost circulation has plagued drilling operations throughout history. Generally the types of formations that are prone to lost returns are cavernous and vugular, naturally occurring or induced fractures, unconsolidated sands, highly permeable and highly depleted tight sands. Well known lost circulation control techniques such as bridging, gelling and cementing are typically used, with varying degrees of success. These remedies can sometimes complicate the problems associated with lost returns. Attempts to cure lost circulation can be difficult and costly, especially when considering the associated non-productive time. The lost circulation problems related to drilling through depleted sands are compounded by the low fracture gradient in the sands and the high mud weight required to minimize compressivefailure in the adjacent shales. For depleted sands, the best way to manage lost circulation is to prevent rather than cure the problem. This can be achieved using a combination of a geomechanics and a fluids approach. A literature survey indicates that significant work had been done in this area [1–13]. Lost prevention materials (LPM) were developed to increase fracture initiation or fracture propagation pressure. Recently, a theory of using stress cages to increase fracturing resistance has been developed and demonstrated successfully in the field[2]. Sand bridging or "smearing effect" that is generated by casing while drilling techniques has also been applied[4].
The variation of sanding onset prediction results with the selection of one or another rock strength criterion is investigated. In this paper, four commonly used rock strength criteria in sanding onset prediction and wellbore stability studies are presented. There are Mohr-Coulomb, Hoek-Brown, Drucker-Prager, and modified Lade criteria. In each of the criterion, there are two or more parameters involved. In the literature, a two-step procedure is applied to determine the parameters in the rock strength criterion. First, the Mohr-Coulomb parameters like cohesion S o and internal friction angle f , are regressed from the laboratory test data. Then, the parameters in other criteria are calculated using the regressed Mohr-Coulomb parameters. It is proposed that the best way to evaluate the parameters in a specific rock strength criterion is to perform direct regression of the laboratory test data using that criterion. Using this methodology, it is demonstrated that the effect of various rock strength criteria on sanding onset prediction is less dramatic than using the commonly used method. With this methodology, the uncertainties of the effect of rock strength criterion on sanding onset prediction are also reduced. Through this study, it is also demonstrated that a sanding onset prediction problem cannot be properly solved by adopting strength criteria that are not influenced by the intermediate principal stress if laboratory test data indicate rock failure is dependent on intermediate principal stress.
Kotabatak field, Sumatra, Indonesia is a heavily-faulted field undergoing an aggressive drilling and development campaign. Nine horizontal wells had been drilled with four more planned in 2008. One of the horizontal wells recently experienced well collapse (and sudden productivity decline) after some time on production, with cavings being flushed out during coil tubing workover operations. In addition to horizontal well drilling, feasibility of open horizontal well completions, hydraulic fracturing design and sanding onset prediction also warranted rock mechanics analyses. To make sound decisions on those issues, building a well-calibrated geomechanical model was critical. In this study, we reviewed the drilling, completion, logging and production information from several wells across the field. We found that (1) The Kotabatak field has a general maximum horizontal stress orientation of NESW. However, there could be localized stress orientation variations depending on structure complexity near a specific well. (2) There was no consistent evidence indicating a significant contrast between the maximum and minimum horizontal stresses. Using a maximum/minimum horizontal stress ratio of 1.05 yielded a consistent calibration result for the wells studied. (3) Sand minimum horizontal stress for the Kotabatak field was calibrated against available closure stresses from hydraulic fracturing and mini-frac data. (4) Rock mechanical properties were calculated with openhole logs based on a Rock Mechanics Algorithm that is closely linked to Chevron's worldwide rock mechanical property database. Consequently, even though there were no core test data available from the Kotabatak field to calibrate rock mechanical properties directly, the log data set provided the means to estimate reliable formation mechanical property values that are consistent with Chevron's worldwide database. Furthermore the entire geomechanical model was calibrated against offset drilling performance measures resulting in a high degree of confidence in the predicted values. Using the calibrated geomechanical model, horizontal well stability predictions were performed and indicated that horizontal sections can be drilled with low mud weight allowing the well to have some yield/failure. Open horizontal well sanding onset prediction indicated that the depth and width of a breakout (or plastic zone if reservoir sand behaves plastically) increase with increasing pressure drawdown. Since water flooding is used in the field to maintain reservoir pressure, sand control may not be needed if an appropriate Bottomhole Flowing Pressure (BHFP) is applied. Introduction The Kotabatak field, Sumatra, Indonesia is a heavily faulted field undergoing an aggressive drilling and development campaign ((Figures 1 and 2). Nine horizontal wells had been drilled (as of the end of 2007) with four more planned in 2008. One of the horizontal wells recently experienced well collapse (and sudden productivity decline) after some time on production, with cavings being flushed out during coil tubing workover operations. In addition to horizontal well drilling, feasibility of open horizontal well completions, hydraulic fracturing design and sanding onset prediction also warranted rock mechanics analyses. To make sound decisions on those issues, building a well-calibrated geomechanical model was critical.
The observed pore pressures and deformations induced by an earth balance shield used to construct the Furongjiang sewer tunnel in soft saturated ground in Shanghai, China, are briefly described. A numerical technique for predicting these pore pressures and deformations is outlined. This approach adopts a coupled viscoplastic-consolidation analysis to describe the time-dependent deformations and strain-hardening behaviour of the soil using parameters obtained from triaxial creep tests. A comparison is then made between numerical results and the results of field measurements, and it is shown that there is encouraging agreement between the calculated and observed response. Key words : tunnelling, finite element, settlements, viscoplastic model, consolidation, field measurement.
Previous research on sand production prediction focused on when sand will be produced during depletion based on some mechanics analyses, but the amount of sand production was ignored. Recently, more and more researchers are focussing on the simulation of heavy oil sand production processes. For an unconsolidated heavy oil reservoir which employs sand production to enhance production, the amount of sand production is of great importance, because too much sand production may cause near wellbore instability, while too little sand production may not maximize well productivity. In view of this, based on both fluid flow modelling and reservoir mechanics concepts, a coupled heavy oil/sand particulate flow/reservoir elasto-plastic deformation model is used to simulate sand production, oil production, and reservoir deformation. With this model, we can determine an optimum flow rate which will not cause near wellbore instability while maximizing well productivity. Introduction Heavy oil sand production as an important production enhancement measure has been used in the primary development of heavy oil reservoirs in Canada for a long time. The production of sand may lead to the change of formation flow-related parameters such as permeability, porosity and mechanical parameters such as cohesion, and it also causes near wellbore stress redistribution. Thus, sand production is a very complicated process involving both fluid flow and geomechanical problems. In order to simulate the effect of sand production and productivity enhancement, simulation of the physical process needs to be done. Because of the long history of cold production, the simulation of cold production is becoming mature and a lot of excellent work has been done by experts in Canada and elsewhere around the world(1–5). Wang(1) developed a model to predict sand production in a heavy oil reservoir in Frog Lake at Lloydminster, Canada. It is believed that reservoir depletion induces stress concentrations around the wellbore, and large drawdown causes a foamy oil zone, in which large drawdown and seepage forces are created which causes sand production. A fully coupled geomechanical, foamy oil flow model was developed. Sand production is assumed to start when the effective radial stress is equal to the tensile strength. Later Wang(2) developed a coupled reservoir-geomechanical model to simulate the enhanced production phenomena in both heavy oil reservoirs (Northwestern Canada) and conventional oil reservoirs (North Sea). It is believed that the production enhancement is contributed:by the reservoir porosity and permeability improvement after a large amount of sand is produced, andby the higher mobility of the fluid due to the movement of the sand particles. Once the reservoir formation yields plastically, loose sand particles can be generated. Sand production has been postulated as a critical condition when the effective radial stress reaches the tensile strength or when the plastic strain reaches the critical plastic strain. Recently, Papamichos et al.(3) and Stavropoulou et al.(4) also provided their model to simulate sand production. Later Papamichos et al.(5) applied successfully this model to interpret sand production from a North Sea reservoir.
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