Valzania, Soraya (ENI E&P) | Kfoury, Moussa (ENI E&P) | Grandis, Marco Giacomo (ENI E&P) | Valdisturlo, Antonio (ENI E&P) | Fanello, Giovanna (ENI E&P) | Guerra, Laura (ENI S.p.A) | Salah, Heikal (ENI) | Amjad, Kashif (ENI Pakistan Ltd) | Sultan, Mir Asif (ENI Pakistan Ltd)
Kadanwari field in Middle Indus Basin (Pakistan) was discovered in 1989 and brought on stream in 1995. The producing reservoirs are Cretaceous Lower Goru sands D-E-F-G. The gas production started from better quality E and F sands; after 2004 layer G started to drain western block of the field, with the first hydraulic fracture job made in Pakistan (well A). Layer G represents a complex target for petrophysical characterization; reservoir sandstones are micro-porosity rich, with variable presence of Chlorite affecting flow properties. Positive results encouraged the operator to drill & frac well B and to consider possibility to extend gas production throughout western block, including sand reservoirs of variable quality, from moderate to tight. The paper describes how reservoir study faced layer G complexity and how production data of wells A and B allowed a post fracjob evaluation integrating well-test data and frac-job interpretations into 3D dynamic model. After history match, the computed GOIP suggested an infilling program in G sand reservoir, with side-tracks of existing wells and new wells, all hydraulically
fractured. So far, one sidetrack and one new well have been drilled; results fully confirmed the complexity of local geological setting. The sidetrack revealed rock quality slightly better than expected (frac not necessary). Pilot well C targeted G-Sand in a sweet seismic anomaly in western area, a gas flare was observed during DST pre-frac. Mini-Fall Off was conducted to estimate closure pressure and effective mobility, but permeability computed from MFO was not conclusive due to important filtrate invasion. DST post hydraulic fracture job confirmed commercial gas rate production higher than 1 MMscfd with a peak of 3.5 MMscfd. The successful pilot well results open new horizon to improve reserve from tight sand of Lower Goru formation.
The objective of this study is to define the physical basis approach to calculate relative permeability of reservoir rocks from image analysis of thin section. Relative permeability is one of the most important parameter and widely used for reservoir characterization. Relative permeability is only measured in the laboratory. To measure relative permeability in the laboratory are expensive and time consuming. Alternatively relative permeability may be estimated from numerical methods such as Lattice-Boltzmann and network modeling. To applying the all method need lot of computational effort and the physical justification of relative permeability estimation remains hidden. A simple and powerful equation to estimate the absolute permeability from porosity and specific surface area is the Kozeny's equation. Darcy's assumption was applied to Kozeny's equation to calculate relative permeability of two phase-fluid flow without introducing any empirical factor. Numerical simulation and image analysis processing technique were applied to check the consistency of Kozeny's approximated relative permeability model. Relative permeability predicted from Kozeny's approximation was compared with permeability predicted from Lattice-Boltzmann flow simulation as well as with laboratory measured data. Relative permeability predicted from numerical simulation and image analysis techniques are well agreed with permeability predicted from Kozeny's approximation. Relative permeability predicted from Kozeny's approximation are also comparable with permeability predicted from Lattice-Boltzmann flow simulation as well as with laboratory measured data. Given permeability model in this study is the physical basis approach and may used to calculated relative permeability from image analysis of thin section.
The paper presents a methodology to develop and apply an equation-of-state (EOS) multi-fluid model for a field in Tunisia. The EOS model was developed by matching measured PVT data for a near-critical oil sample. The fluid characterization was used to estimate contamination level in oil-based-mud contaminated MDT samples, calculate decontaminated sample composition, estimate zone composition based on clean-up test measured oil-gas ratio, estimate fluid composition of some layers where samples were not available, and study the effect of gas condensate blockage and capillary number on simulated well performance.
In this field, reservoir fluids range from lean gas condensate to rich gas condensate and volatile oil. Clean up tests were conducted for all four zones encountered in the well, and oil-gas ratios were measured. During the clean up test of one zone, a near critical oil sample was collected and standard PVT experiments were conducted. Oil based mud (OBM) contaminated MDT samples were collected from six of the nine non-communicating layers, with OBM contamination levels between 20-65 wt% STO.
An EOS model was developed after matching measured PVT data on the near-critical oil sample. The MDT samples were decontaminated using measured mud composition. The calculated decontaminated "clean?? sample compositions were used in a reservoir simulation model to initialize the layer from which the MDT sample was taken.
The developed EOS model was also used to estimate the fluid composition of different zones and layers without fluid samples. The zone fluid compositions were calculated based on measured test OGR. The EOS model, zone fluid compositions, decontaminated MDT samples, and layer mobilities were used to estimate fluid composition of the layers without samples.
This paper provides a methodology that can be used in any other field.
Optimizing the exploitation of fractured reservoirs requires a reliable characterization of the most influential heterogeneities on flow properties. To this end, reservoir simulation models should remain interpretable in geological terms. Workflows are available (i) to construct geologically-realistic models of fracture networks, (ii) to turn these models into simplified conceptual models usable for field-scale simulations of multi-phase production methods. However a critical step remains that of
characterizing the flow properties of the geological fracture network. The multiscale nature of fracture networks and the associated modeling cost impose a scale-dependent characterization: (i) multi-scale fractures are characterized in local dynamic tests area, e.g. well test drainage area, through the calibration of geologically-realistic Discrete Fracture Network (DFN) models and accurate local flow tests simulations; (ii) large-scale faults are characterized through reservoir-scale production history simulations. This paper presents an efficient "multi-mode" inversion methodology to facilitate the characterization of fracture properties from well test data. The fracture model is optimized sequentially according to different modes of deformation. First, the parameterization is defined such that the fracture model is deformed as a whole (mode 1), then S fracture sub-sets are defined accordingly to their sensitivities to well test data (mode S), where S is increased sequentially. The optimization is performed via an original evolutionary algorithm that has been coupled with a 3D DFN flow simulator. An application is presented on a fractured reservoir model having two facies, four fracture sets and involving a horizontal well test. The characterized fracture properties are the mean size properties, mean conductivity and faciesdependent fracture densities.
This "multi-mode" inversion methodology is shown to be much faster to characterize physically meaningful and dataconsistent fracture properties, compared with a direct optimization application on all model parameters. This methodology facilitates the characterization of fractured reservoirs flow properties.
For a deepwater operator facing the challenges of directional drilling and wellbore stability, surveying with high spread costs in excess of USD 1 million per day, any approach which promises to reduce or eliminate cost and risk has great potential benefit. This paper showcases how careful planning, a fit-for-purpose survey program, and, most importantly, an effective, real-time geomagnetic referencing service (GRS) can significantly improve the operator's ability to hit both geological and financial targets. The authors describe recent breakthrough improvements in the accuracy of GRS techniques and present a case study to illustrate the benefits of this approach for the industry, especially in deepwater operations.
Each magnetic survey tool has an associated degree of uncertainty in the accuracy of data acquired. This error is cumulative, increasing with depth as a well is being drilled. In three dimensions, this area of uncertainty takes an elliptical form around the projected well path, a zone of possible well positions known as the ellipse of uncertainty (EOU). In high-angle wells, the EOU may grow so large that it exceeds the dimensions of the geological target, decreasing the driller's level of confidence and increasing the risks and potential costs of missing the target. Therefore, the development of more accurate yet cost-effective surveying techniques has become increasingly critical.
The authors will describe a survey approach that meets this challenge by incorporating breakthroughs in real-time GRS and which offers the producer the following benefits:
- Achieving planned geological targets
- Saving the cost of running gyroscopic surveys
- Avoiding costly post-gyro well path corrections by staying on-path in real time
- Preventing stuck pipe, lost time, and other risks often associated with gyro surveys
The example case to be discussed illustrates how to realize all of the above benefits.
Rigorous validation of a simulation model of the THAI -Toe-to-Heel Air ijection process has been performed using results obtained from a 3D combustion cell experiment on Athabasca Oil Sands. The numerical model includes a new kinetics formulation, based on the Athabasca thermal cracking kinetics scheme proposed by Phillips (1985). The kinetic model excludes low temperature oxidation, since THAI operates in a high temperature oxidation mode. Excellent agreement was obtained between the predicted and experimental oil production rate, and there was generally a good match obtained for other dynamic variables, including the residual coke profile, produced oxygen, and peak combustion temperature. The numerical model provides a fundamental platform for upscaling to field scale, that will enable fine scale details of the process to be captured.
Simulations were performed under dry in situ combustion conditions at the high air injection fluxes used in the experiment. Under these conditions, vertical-plane temperature profiles in the sandpack confirm that the combustion front is quasi-vertical and forward leaning in the direction of the heel of the horizontal producer well. The shape of the combustion front was predicted more accurately from horizontal-plane profiles, which showed that there was no oxygen in regions ahead of the combustion front. Oil displacement occurs mainly by gravity drainage, but pressure draw down in to the horizontal producer well below the Mobile Oil Zone (MOZ) is also significant. Various zones that develop during the in-situ combustion process include a ‘Steam Zone', and this is located upstream of the Mobile Oil Zone (MOZ). All of the mobilized oil is produced from the MOZ, which comprises two regions. The first part contains oil produced by thermal cracking of the heavy residue and vaporized ‘lighter oil'. The main bulk of the oil produced in THAI comes from the second region of the MOZ, containing ‘banked' original oil. The oil which is eventually produced is partially upgraded oil, due to the thermally upgraded and ‘lighter oil' fractions mixing with the original oil when they enter the horizontal producer well.
Intelligent well technology is a relatively new technology that has been adopted by many operators in recent years to improve oil and gas production, and recovery. The technology uses downhole monitoring and control to regulate flow condition and provides solutions to production problems. It is one of the most effective means for optimization of commingled multilateral wells in heterogeneous reservoirs. Due to the high cost and complexity in intelligent multilateral well constructions, accurate modeling of the reservoir, completion and wellbore performance is essential to design an economically beneficial well, and the critical component, inflow control valves (ICV), should be integrated into the performance modeling process.
This paper presents an integrated analytical model that is built on existing models for predicting reservoir and wellbore flow behavior. Also, equations that can predict the flow performance through restrictions such as ICVs, in a multilateral well system are incorporated into the analytical model. The integrated model estimates the reservoir inflow and flowing wellbore pressure at each lateral of a multilateral well, then predicts the anticipated pressure drop across each ICV for any given flow rate. By knowing pressure and flow distribution in a well system, the flow rate distribution can be balanced by operating ICVs to achieve better flow conditions. This analytical model provides the engineers with a hands-on tool to select proper ICV positions for each lateral or segment and helps optimize the well production. Examples at field conditions are used in the paper to illustrate how the model can be used to improve well performance. Applications such as preventing crossflow in commingled multilateral wells are also presented in the paper.
Winarga, Kanuga (EMP Malacca Strait) | Dewanto, Christianto Widi (Caltex Pacific Indonesia) | Erwin, Erwin (EMP Malacca Strait) | Gholib, Ramadanus (EMP Malacca Strait) | Wahono, Teguh (EMP Malacca Strait/Kondur Petroleum S.A.)
Historically, squeezing cement into 9 Interval Perforations in one procedure is almost never happen in actual operation but in August 2010 we did it in Mengkapan Field and finish with success.
Previously in the Melibur oil field in Sumatra, Indonesia, three or four cement-squeeze jobs have been required before the zone holds pressure. Failure was thought to be due to gaps remaining after the squeeze-cementing job between the oil-wet matrix rock and the water-based cement.
This paper will tell a success story in Mengkapan Field by squeeze out 9 interval perforations (850 ft height) in one shot with a surfactant soak that was used to increase the squeeze-cementing success rate. The function of the surfactant was to mobilize trapped oil by creating an emulsion, and to change the oil-wet rock to water-wet rock.
The surfactant was injected into the rock formation and allowed to soak for 24 hours. Then the squeezecementing job was performed as usual. This surfactant soak was trialed in three wells, and they passed the pressure-holding test after an average of two squeeze-cement jobs.
It was concluded that surfactant treatment is a great solution to increase squeeze cementing quality, and is now standard practice in this field.
Pasca-trial and error water shut off program with squeeze cemented watered-out-perforation zone in several onshore shallow wells, more bigger challenge is how to apply into high profile well such in offshore. In company's contract area, there is one offshore field with +/- 6000 ft measured depth and many of interest zones.
After so many years, almost all of interest zone has already perforated. With those conditions, one of the ways is drawdowning the well dramatically to flow the oil to surface. And in some point if some how the artificial lift system (such as ESP) fail, the well will lost their economical value (the oil rate is no longer cover operating cost well) to be workovered.
Poor macroscopic sweep efficiency can be a problem in CO2-flooding of oil reservoirs. The macroscopic sweep efficiency can be low due to the combination of high mobility ratio, gravity segregation and heterogeneity. By decreasing the mobility of CO2 the macroscopic sweep efficiency can be improved. In the present work the surfactant, alpha olefin sulphonate (AOS), has been used as CO2 foaming agent. Dynamic flooding experiments have been carried out at realistic reservoir conditions to study the relative transport of water, CO2 and surfactant when foam is generated in the porous network. The surfactant has been labeled with the radioactive sulfur isotope 35S. The water has been labeled with the radioactive hydrogen isotope tritium (3H) and the CO2 has been labeled with the 14C isotope.
It is shown that the flow of the individual phases in a CO2-foam flooding can be monitored by using of tracer technology. Variations in the flow rates of surfactant solution and CO2 can be clearly detected, and the accessible pore volume can also be determined. AOS products contain different chemical structures. In the study, the main AOS components have been chemically separated prior to injection on the porous column. The transport of the individual components was shown to be different. In the reservoir, chromatographic separation of the AOS components may change the efficiency of the foam process.
The study has shown that use of tracer technology can be a powerful tool in study of transport mechanisms in CO2-foam flooding.
Unexpected high water cut, sand production and low productivity have negatively affected multiple wells producing from reservoirs in the Apure Area fields of southwest Venezuela. As a result, multiple well interventions have been conducted which increase costs and delay oil production. Several of these wells are inactive today but could be potential candidates for reactivation by reperforating prospective intervals. In several cases, the selection of the perforated interval for these reservoirs is considered inefficient because the effects of multiple dynamic and static petrophysical properties are not considered in the current method, such as vertical permeability, anisotropy or pore throat size, among others. We propose a systematic analysis to optimize the interval to be perforated for inactive and new wells that will minimize such related production problems.
The proposed analysis involves the incorporation of multiple variables (type of perforation, interval to perforate, distribution of reservoir fluids, fluid of completion, etc.) to consider the effects of the different petrophysical properties on well productivity. The latter are obtained by integration of rock-core data and conventional and advanced well logs acquired in open and cased hole. In addition, we conducted a sensitivity study to analyze other parameters, such as perforating method and production behavior. A technical analysis was performed to select the optimum design based on different conditions leading to a complete study. The results show that the optimum interval selection and type of perforation to be implemented should not involve only a simple net pay consideration but also multiple factors such as reservoir properties, reservoir fluids distribution and perforating method that play a key role in well production behavior. Finally, we present field applications that confirm the success of this method that enables the reliable selection of an optimized perforated interval.