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.
Injection of water with solid and oily particles happens during waterflooding using seawater, produced water and other waters of poor quality. The injected particles are captured by porous rock causing decrease of permeability, cake formation and consequent injectivity decline. Maintenance of the injection rate results in increase of pressure gradient near to well.
We consider effects of mobilization of residual oil in well vicinity due to increase of pressure gradient and, consequently, the increase of capillary number. The mobilized oil ganglia perform snap-off and release oil drops that move together with the injected particles; they are captured by porous rock causing additional formation damage.
In the current work a simplified analytical model that covers effects of oil drops generation and additional permeability reduction is developed. The model includes analytical expressions for deposition profiles, breakthrough curves and permeability decline. It was used for planning and design of laboratory test on injection of oily water into residual-oil-containing core.
The sensitivity study was performed with regards to flow velocity, injected concentration and formation damage parameters. The main result is an additional formation damage induced by particles released by residual oil.
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.
Well productivity impairment due to two-phase flow in the near well region is a major concern in gas condensate reservoirs. There usually exhibit complex flow behaviours due to the condensate banking around the well caused by the bottom-hole pressure drops below the dew point (for most gas-condensate reservoirs). This leads to a drop in gas relative permeability, a decrease in gas production and a significant economic condensate remains in the reservoir.
In this study, we use a methodology to evaluate the productivity of gas condensate wells. Starting from the analysis of six available well tests, we have identified one test that most suitable for the aim of this project. Then we have used a well-developed workflow in the Institute of Petroleum Engineering at Heriot-Watt University to carry out the study. The workflow is to first characterize the formation for reservoir heterogeneity, the fluid properties and well productivity to evaluate the well dynamic performance (transient pressure and inflow). The formation evaluation of the well is performed to determine key parameters of the reservoir. Then fluid PVT test results are studied in details for reservoir fluid property in contrast to the phase diagrams for the whole gas column. The nature of the test, i.e. a gas-condensate reservoir with respect to the testing depth, interval and pressure regimes (on the phase diagram) have been re-ensured.
A radial homogeneous model was built to tune the well test simulation local grid refinement cell sizes and time steps, and a 3D geological model was built using the latest techniques to honour the reservoir heterogeneity. The model was then up-scaled into a fully compositional flow model for well test simulation. Numerical well test has been conducted with the same testing schedule and parameters (rock and fluids) as the existing well test. Finally, sensitivity studies on key parameters have been performed through the numerical well test simulation leading to the construction of families of reservoir system type curves. By the matching of these type curves to the existing well test, a numerical model is derived by tuning and matching to the real testing data. The derived model then can be used for future productivity forecast, as well as for new testing design.
A well test interpretation completed in this way has greatly reduced the analysis uncertainty and enhanced the understanding of the testing and the reservoir providing much more value from a well test.
Most of the oil production in the Middle East comes from carbonate reservoirs, the majority of which are fractured. These reservoirs tend to produce at high rates in their early production period followed by low rates later on, leading to low overall recovery. The challenge is to manage the field and arrest the production decline for a long time.
A reservoir simulation study was performed on a fractured Middle Eastern carbonate field to determine the optimal production strategy. Three possible scenarios - natural depletion, gas injection and water injection were compared. Results indicated that water injection yields better recoveries than gas injection and natural depletion; this is expected since the rock is intermediate to oil-wet, meaning that there was high recovery from imbibition in water flooding. The presence of connected fractures led to early breakthrough and low recoveries in gas injection scenarios. The different physical mechanisms affecting oil recovery are discussed and recommendations are made for other fields with the same fracture properties and wettability
This article introduces a multiscale pore structure characterization method using a combination of mercury porosimetry and image analysis. The method was used to determine the distribution of pore volume by pore size and to estimate the pore-to-throat size aspect ratio. The key idea of the method is that pore size distribution obeys a fractal scaling law over a range of pore size. On this basis, scattering intensity data computed from the measured two-point correlation function and those measured from mercury porosimetry are extrapolated in the size range 0.01 µm < r < 1000 µm, using the known fractal scaling law.
A set of siltstone samples taken from Daqing Oilfield was analyzed through this method. Distribution of pore volume by pore size over the entire range of pore length scales was determined. The results demonstrated significant similarities in the pore structure of all samples. The image analysis results were in qualitative agreement with the results of mercury intrusion/extrusion tests.
The results were also compared with some other samples (including siltstone, sandstone, and dolomite) that had been analyzed using similar methods. It is shown that the surface fractal dimension obtained by analysis of MIP data is consistent with the value obtained by image analysis for different samples with different porosity and permeability.
Novel information on the pore-to-throat aspect ratio is obtained by comparing the complete pore volume distribution (PVD) to the MIP data.
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.
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.
Following the reengineering of ENI's Development Management System, which occurred in the early 2004, ENI has developed an IT integrated Project Management System to support Field Development Projects.
ENI's Development Management System promotes a stage&gate approach to the development of a field, starting from the assessment of the value of the field, the identification of the viable development scenarios, the definition of the selected development strategy and the execution of the project (including the construction of the facilities and the hand-over to operations). At the end of each stage, a predefined set of data and documents have to be prepared by the project team to be submitted to a Decision Gate in order to support an informed decision by ENI's executives and authorize the start of the following phase.
The IT system has been developed with a Web Portal technology and it assists:
the multidisciplinary team involved in the project (geologists, reservoir and drilling engineers, facility & construction specialists, HSE consultants) in the daily work. In fact, it provides web based tools to share and verify project documents; develop and control the schedule baseline of the project; automatically track cost expenditures against budget values; document and review risks and lessons learned; manage milestones, issues and project changes;
the executives involved in decision making. In fact, it provides a high level dashboard with an integrated visualization of the last updated schedule and cost figures for the project, as well as direct access to the main project documents relevant for the Decision Gate of the current project phase.
The system integrates the document management capabilities of Domino; extends the planning and control functions of MS Project; automatically imports the budget/actual expenditures from SAP R3; authorizes and profiles users according to their role. It has been used to support 50 project phases across 34 projects.
The environmental concerns, increasing cost of exploration and the technical requirement of high temperature drilling demand the use of environment friendly, economically attractive and thermally stable water-based drilling mud to fulfill the functional behavior of a mud system to complete a well safely and economically. Thermal stability of low cost water-based mud is essential to achieve the technical goal, meet the environmental challenges and reduce the mud cost. This paper describes a novel additive to prevent the thermal degradation of bentonite mud up to a bottom hole temperature of 150 °C.
The experimental data of a base bentonite mud showed more than 150% increase in PV, more than 250% increase in YP and more than 100% increase in gel strength after hot rolling at 150 °C for 16 hours. The bentonite mud with novel thermal degradation inhibitor showed about 50% increase in PV and little change in the YP and gel strength characteristic of the bentonite+GSP mud after hot rolling at 150 °C for 16 hours. The environment friendly thermal degradation inhibitor is expected to increase the working temperature range of bentonite mud without causing any damage to the environment.