A simulation model for the tracer response analysis in naturally fractured reservoirs was developed by double-continua formulation. Waterflooding in dual-porosity dual-permeability reservoirs is first modeled by the streamline approach. Then flow of the water-soluble tracer described by the coupled convection-dispersion equations is combined. First, 1-dimensional convection-dispersion equation is solved along each streamline in the matrix and fracture systems by ignoring the gravity and transfer terms. The concentrations are mapped onto the grid, and corrected with gravity and transfer.
The model is capable of conducting tracer flow and waterflooding simulation in field-scale dual-porosity dual-permeability systems. It is developed particularly for analyzing multiple-well tracer tests in heterogeneous fractured reservoirs.
The model is validated for homogeneous and heterogeneous permeability distributions comparing with results from Eclipse. Effectiveness of the CFL condition and a TVD scheme to control stability and numerical dispersion are evaluated and analyzed. In the heterogeneous case, the saturation fronts and tracer responses from the model are less smeared than those from Eclipse. The model is also run for validation and sensitivity cases with different dispersivity.
Finally, tracer responses for a multiple injection/production scheme in a realistic reservoir including mega-fractures are simulated. Simulations demonstrate the potential of the streamline approach for characterizing heterogeneity of the fractured distribution, and for identifying flow paths.
Evaluation of heterogeneous fracture developments is critically important for assessing the reservoir performance, and yet remains to be a difficult issue. Tracer flow simulation by the streamline approach is particularly useful to interpret and model fracture-matrix systems in terms of flow properties and anisotropy. The streamline-based model is powerful for analyzing tracer response data with readily available visualization.
Dual porosity numerical models are widely adopted in the oil business to model the performance of complex systems characterised by two different porous media. However, for numerical models of a certain complexity due to the large number of active grid-blocks, the dual porosity approach is often computationally unaffordable especially when a compositional formulation must be used.
This paper describes the methodology that was developed to mimic the dynamic performance of a complex triple porosity system by means of a single porosity model. The three porous systems were the matrix blocks, the fracture network and the dissolution karst bodies. The methodology was derived for a complex massive carbonate field not yet producing which is currently envisaged to be developed via miscible gas injection.
The matrix and karst bodies were statically modelled independently from the fracture network system. The characterisation of the fracture network has been driven using a DFN approach by integrating seismic, continuity cube interpretations and well data, such as FMI and mud losses. Due to the lack of dynamic data, the fractures' petrophysical properties were calculated from correlations. The matrix, karst bodies and DFN derived fractures were then up-scaled to a dual porosity model. The dual porosity model dynamic performance was considered as the reference to be matched by an equivalent up-scaled single porosity model.
An innovative procedure to up-scale matrix, fracture and karst properties into the equivalent single porosity model was tested for both a natural depletion and a miscible gas injection scenario. The methodology was firstly evaluated in representative sector models and then extended to the full field model. This methodology resulted to be very efficient being able to reduce the simulation time and model complexity drastically while capturing all the dynamic key performance indicators of the more complex and computationally expensive dual porosity model.
Tyrihans is an oil and gas-condensate field offshore Mid-Norway. Oil reserves are 29 million Sm3 and gas reserves are 35 billion Sm3. The field will be developed as a subsea project with 5 templates having 9 producers and 3 injectors. Production start-up is July 2009.
The field development is innovative in the following aspects:
Cost effective development with a 43 km tie-back to the Kristin platform through an 18?? pipeline. Tie-back is possible because the pipeline will have direct electrical heating to prevent formation of hydrates and to preserve temperature.
Pressure support with both gas injection and raw sea water injection. This is feasible by installing two water injection pumps subsea and using available power and compressor capacity at neighbouring fields.
Extensive use of advanced wells. The oil producers are dual-lateral with approx. 1.5 km horizontal reservoir sections, equipped with down-hole ICVs (Inflow Control Valves) and gas lift. Both main bore and laterals will have 8.5?? hole diameter, made possible by using 8?? expandable liners
Important reservoir management and simulation issues are:
Tyrihans consists of two structures, which cannot be produced independently. Handling gas and water coning in a two-front system and keeping track of fluid contacts are challenging.
The northern structure consists of an 18 m thin oil zone with a gas cap. To simulate recovery from thin oil zones is challenging. The simulation model has horizontal grid, in order to have the required vertical resolution of the oil zone.
Correct modelling of pipeline flow and flow assurance.
The long, single pipeline tie-back makes well testing difficult. Reservoir monitoring and management must then be based on subsea flow meters and gauges. Production optimization will be performed from an onshore support centre.
With the chosen reservoir development strategy high recovery is obtainable. The simulated oil recovery in the southern part is 52%, and the gas recovery in the northern part is 80%.
Tyrihans is an oil and gas condensate field offshore Mid-Norway (Figure 1). Tyrihans Sør (South) was discovered by well 6407/1-2 in 1982 as the first discovery on Haltenbanken offshore Mid-Norway. The well test showed a rich gas-condensate. Tyrihans Nord (North) was discovered the following year, proving a gas cap with a thin oil zone. An appraisal well in Tyrihans Nord in 1996 was drilled through the OWC and proved an 18 m thick oil column. In 2002, an appraisal well in Tyrihans Sør showed a 35 m oil column below the gas cap. With total in-place volumes of 71.4 million Sm3 oil and 57.4 billion Sm3 gas, an independent development of Tyrihans was not economical feasible. In the meantime, the neighbouring gas-condensate field Kristin was under development. It was decided to develop Tyrihans as a subsea (SS) field, tied back to the Kristin platform.
A subsea development makes investments in a platform/vessel unnecessary. However, long tie-backs are challenging with respect to oil recovery and flow assurance. This paper will focus on the SS development facilities and how high oil recovery will be obtained on Tyrihans.
Proxy models are becoming more widely used as they can simplify highly complex processes with reasonable accuracy. Especially in risk analysis, where complex relationships between the uncertainty parameters exist, proxy models are used in form of response surfaces to accelerate interpretation and optimization methods. However, the use of proxy models is rarely seen in production optimization.
When the data gathering from wells and surface equipment is fully automated, production optimization can be performed almost in real-time. The bottleneck in this workflow is the high computational effort of simulation models and the large number of input variables to optimize. This disadvantage can be overcome by mimicking the behavior of the system, such as the coupling of a simulation model and the surface network model, by using a computational efficient method. The requirements for such proxy models are high, since they have to capture highly non-linear trends hidden in a small number of representative samples.
This paper presents the usage of neural networks as proxy models. For the production optimization process, genetic algorithms are used. Their advantage lies in the ability to handle a large number of input variables. The neural network operates as fitness function for the genetic algorithm. The optimization result can be achieved extremely fast (within seconds), allowing optimization in near real time. A real life example is also presented in this work.
Jiang, Tingxue (RIPED of PetroChina) | Zhang, Yiming (Huabei Petr. Admin. Bureau) | Wang, Yongli (RIPED of PetroChina) | Ding, Yunhong (Langfang Branch of RIPED) | Luo, Ning (PetroChina Co. Ltd.) | Xu, Zejun (Huabei Oil Field Corporation,PetroChina) | Feng, Xingkai | Zhang, Hongmei
A hydraulic fracturing technology is put forward in clay-carbonate reservoirs whose characteristics (take well A as an example) are: 1) deep well depth (4237.5m), high temperature (146?), high pore pressure (42MPa); 2) high content of clay (15-22%) and high content of velocity-sensitive minerals (54-71%) such as illite and kaolinite; 3) horizontal stratifications are richly distributed as well as some natural fractures or cavities with high angles; 4) the matrix has a ultra-low permeability(0.0087-0.022×10-3µm2) and ultra-low oil saturation (12.3-18.3%). Consequently, the highlights of the hydraulic fracturing technology are: 1) a new fracturing fluid is developed using a super grade Guar as its densifier, with the viscosity of the base fluid being 93 to 102 mPa.s, while the residue content of 197 mg/l. 2) two types of high strength ceramic proppant are used, one is 20/40 mesh, the other is 40/60 mesh; 3) a new kind of mini-fracturing technique is utilized to determine the well head pressure under various pumping rate, near well bore friction pressure, loss coefficient and decrease reservoir temperature and control fracture height as well; 4) a new optimization technique of fracturing treatment parameters is developed systematically,. such as systematic laboratory tests for the fine evaluation of formation, strategy to avoid multiple fractures, monitoring technique of bottom hole pressure, etc.; 5) a new strategy is adopted to help flowing back of fracturing fluid, which takes the stress sensitivity near the well bore and natural fractures' influences in to account. What's more, the technology has been put in to filed application in the well A, the fracturing treatment is success and the post-fracturing performance is satisfied. Summarily, a systematic fracturing technology is put forward adapted to clay-carbonate reservoirs, and it has a great significance in the near future especially in China.
We adapted a scratch apparatus used to evaluate shear strength and stiffness of rocks to use on soft filter cakes, to obtain quantitative information on cake properties for modelling purposes. The modelling will help design better drilling fluids, in terms of their filter cake's resistance to oil production onset. Scratch testing of rock specimens is now a well established method to obtain reliable strength and stiffness measurements as a function of distance along the scratched surface. The apparatus consists of a rigid frame holding a cutter, being pushed at a constant velocity over a rock specimen. A micrometric screw allows the user to choose a precise cutting depth, while a bidirectional load cell monitors the shear and normal forces on the cutter. The shear force can be related to the specific energy of cutting, which in turn correlates with the Unconfined Compressive Strength (UCS) of the rock. New low-resolution load cells have been installed in anticipation of the orders of magnitude lower expected values when scraping filter cakes. Rocks were exposed to different fluids to assess the impact on filter cake quality and inner filter cake properties. The effect of the internal filter cake on the rock was also addressed by scratching the rocks prior to filtration and once again after, scratching through the filter cake, on the exposed rock face. Quantitative and detailed probing of filter cake elastic properties is now possible using the scratch method. Concerns about removing the filter cake all at once (especially when OBM systems are tested, known for their low adhesion) turned out to be unfounded; the tool was capable of scraping out clean, well-defined cake layers, down to a thickness of 0.1 mm.
Recently our business has had great success in developing tools for using full physics simulators in Assisted History Matching (AHM) and prediction of future performance. However, the end user is often left wondering what to do with the large number of forecasts from these studies; any optimisation of the remaining potential has to be done manually.
This paper discusses a method in which the principles of AHM are used to optimise the development. In AHM the practitioner attempts to minimise the error between the observed and simulated data; the ‘objective function'. A large number of ‘geological' variables to the simulator are sensitised. ‘Control' variables are used in the predictive work. These are only limited by the scheduling features of the reservoir simulator and would normally be the number and location of development wells; change in facilities constraints; re-completion; workovers etc. The objective function for development optimisation tends to be an economic one, i.e. Net Present Value (NPV) or some other profitability indicator. The method described in this paper has an advanced feature for generating additional results based on the simulator output time series.
Schedule optimisation is known to be a very difficult problem, not amenable to standard mathematical programming algorithms, and we describe how, in conjunction with the use of a proxy model, we have successfully applied genetic algorithm optimization techniques, to solve the scheduling problem with minimal CPU processing.
The method has been used a number of times and its application is described by some case studies; optimising the number and location of development wells and timing of scheduling events. As a very large number of possible combinations of variables are used the optimisation tends to be less subjective than a manual giving generally better results.
Zachariassen, Eli (Norsk Hydro) | Meisingset, Hilde (Norsk Hydro) | Otterlei, Cecilie (Norsk Hydro) | Andersen, Trond (Norsk Hydro) | Hatland, Kim (Hydro) | Hoye, Trond (Hydro) | Mangeroy, Gro (Hydro) | Liestol, Frode (Hydro)
A work flow to improve the modeling of a fluvial reservoir is presented. Modeling of fluvial reservoirs can be very uncertain when only conditioned to well data. By utilising 3D and 4D seismic inversion data to condition the geological model, the uncertainty in the facies distribution is reduced. Cross plot of 3D elastic inversion data predicts facies better than acoustic impedance data or Vp/Vs data individually. By including 4D elastic inversion data, the correlation between the classified facies from seismic and the facies zonation in the wells, is further improved. A sand probability cube is computed from 3D and 4D elastic inversion data, and used to condition the geological model of the fluvial reservoir. Upscaling and flow simulation are carried out on a set of realisations. This results in a range of simulated production profiles. The dynamic information in the 4D seismic is then used to rank the realisations by comparing the real 4D data with forward modelled elastic parameters from the flow simulation model.
The described work flow is a new way of integrating different types of data in the modeling process in order to reduce uncertainties.The method is applied to the fluvial Ness reservoir in the Oseberg field in the North Sea.
Qi, Zhilin (Zhongyuan Oil Field) | Du, Zhimin (Southwest Petroleum Inst.) | Liang, Baosheng (Univeristy of Texas at Austin) | Tang, Yong (Southwest Petroleum University) | Wang, Shouping (Research Institute of Petroleum Exploration and Development, Zhongyuan Oil Field) | Deng, Ruijian (Research Institute of Petroleum Exploration and Development, Zhongyuan Oil Field)
As a type of complex well, snaky well is pretty promising especially in the geometrically complicated reservoirs and has been reported recently. Accurate prediction of well productivity is vital. However, conventional productivity calculation methods for horizontal wells could not be applied directly for snaky wells because the production part in the well bore has large fluctuation in the vertical direction and therefore the wellbore pressure drop should not be neglected.
On the basis of the distribution of velocity potential produced in an infinite reservoir by one snaky well, this paper uses the mirror image and the principle of superposition and obtains the velocity potential and pressure distributions for bottom water drive reservoirs with and without gas cap, and edge water drive reservoir. Along the well bore, we then study the flow characteristics and establish a pressure drop model. Coupling wellbore flow with fluid flow in the formation, we develop and further solve a productivity model for the snaky well.
The high precision and practicability are clearly demonstrated using an example. Such well productivity approach reduces uncertainty and better satisfies the real condition, resulting in more accurate prediction.
Capillary pressure and relative permeability are important parameters in reservoir engineering. Techniques frequently used to measure capillary pressure and relative permeability simultaneously are complicated and time-consuming. On the other hand, it is also difficult to measure the two parameters in low permeability rocks. It would be useful if capillary pressure and relative permeability could be inferred from spontaneous imbibition tests. This is because such tests are relatively simple, fast, and economical. In the present study, an analytical approach was developed to determine capillary pressure and relative permeability simultaneously by using experimental data of spontaneous water imbibition into gas-saturated rock. Spontaneous water imbibition tests in different rocks were conducted to test the proposed approach. Both capillary pressure and relative permeability were calculated using the proposed approach and the results were closely equal to those measured using different methods.