Encouraging Preliminary Results of Steam Flood Pilot Project in Unconsolidated Reservoir with Strong Water Drive, Sultanate of Oman

2021 ◽  
Author(s):  
A. A. Qassabi
Keyword(s):  
Simulation Models ◽  
Pilot Project ◽  
Steam Injection ◽  
Production Performance ◽  
Surveillance Program ◽  
Sultanate Of Oman ◽  
Productivity Improvement ◽  
Cyclic Steam Stimulation ◽  
Production History ◽  
Steam Flood

Observed performance of the specially designed steam flood pilot project (implemented and currently operating in the unconsolidated, strong water drive and relatively deep of Mesozoic Sand reservoir in IXYZM Field, Sultanate of Oman) indicates encouraging results of thermal EOR. This reservoir has been produced under primary cold production with horizontal wells but production history and simulation models indicate that ultimate recovery, even with dense well spacing, will be limited to less than 15% of OOIP. Cyclic steam stimulation has been applied in several wells prior to steam flood pilot implementation to confirm steam injectivity and productivity improvement. Reservoir simulation and analytical analysis led to the design of a two-pattern pilot using 2 vertical injectors and 3 horizontal producers. Steam injection started in late 2018 and a complete surveillance program is undergoing to monitor all key parameters related to injection and production performance.

scholarly journals The Effect of Regular and Long Cyclic Steam Stimulation Method on Oil Production Performance of RUA Field in Central Sumatera

2020 ◽  
Vol 43 (1) ◽  
pp. 7-15
Author(s):  
Intan Permatasari ◽  
Tomi Erfando ◽  
Muhammad Yogi Satria ◽  
Hardiyanto Hardiyanto ◽  
Tengku Mohammad Sofyan Astsauri
Keyword(s):  
Heavy Oil ◽  
Oil Production ◽  
High Viscosity ◽  
Production Performance ◽  
Reservoir Temperature ◽  
Cyclic Steam Stimulation ◽  
Production Wells ◽  
Production History ◽  
Stimulation Method ◽  
Cyclic Stimulation

RUA field is classified into heavy oil reservoir type due to the high viscosity value and low API degree . This causes the RUA field can not be produced conventionally. the solution of this problem is to apply steam or thermal injection into reservoir which could reduce the viscosity of the heavy oil (Bera Babadagli, 2015). One of the best EOR methods that has been proven to overcome this issue is using CSS method (Suranto et al., 2020). During the production period, the CSS process can affect the viscosity of the oil by increasing the temperature of the oil in the reservoir. In one production well, cyclic work are applied periodically, its called repeated cyclic (J. J. Sheng, 2013). This is because time of reservoir temperature stays above the baseline temperature reservoir shortly. Even though the cyclic already done repeatedly, there is still a decrease of oil production, different peak reservoir temperatures, and found the possibility of pump damage after the cycle job which led to the need for analysis on these issues. The analysis was performed by looking at the historical production data, historical reservoir temperature data, and production pump work data in the RUA field. After a production history data that reprsentative analyzed, it was found that teh production after cyclic there is increasing, and there is also a decline from the previous cyclic production. Based on the results of the production analysis, it was found that 53.24% of the production wells in the RUA field were already in the ramp down stage and 46.75% were already in the ramp-up stage. Meanwhile, the average HET for regular cyclic jobs is 3-4 months and 5-6 months for long cyclic jobs. And from the pump work data, only 3 wells were damaged. This suggests that cyclic stimulation is completely safe to be performed in this field.

Improvements in understanding short-range permeability variability in coal seam gas reservoirs

2016 ◽  
Vol 56 (2) ◽  
pp. 555
Author(s):  
Stephen Tyson ◽  
Suzanne Hurter ◽  
Fengde Zhou ◽  
Morteza Jami
Keyword(s):  
Short Range ◽  
Simulation Models ◽  
Holistic Approach ◽  
Predictive Modelling ◽  
Gas Production ◽  
Production Performance ◽  
Improve Measurement ◽  
Production Wells ◽  
Production History ◽  
The Impact

After several years of production history on at least some of the more than 7,000 CSG production wells in the Surat and Bowen basins, reservoir engineers continue to note that understanding detailed permeability spatial variation near the well bore and its impact on actual production performance remains poor. There is a growing realisation that permeability of coals has an even higher variability than was initially expected, and that this variability occurs across a shorter range than that of the typical inter-well spacing (~750 m). As a result, flow between wells, pressure depletion, water and gas production rates and ultimate recovery is difficult to predict. Forecasting short-range continuity of different categories of absolute permeabilities through modelling is the key challenge. Other physical or geophysical parameters may change similarly with the same range. Generation models tend to over-estimate the lateral continuity of coals and associated carbonaceous shales resulting in a poor match between the model predictions and the observed production data. This may be due to incomplete information on the short-range variability of porosity and permeability and the appropriate up-scaled values for these parameters used in the reservoir simulation models. This extended abstract discusses controls on permeability, both the geological influences and the impact of drilling and completion on permeability. Taking a holistic approach to the problem of understanding permeability variability, the relative impact of these controls is estimated and discussed. With the benefit of rudimentary ranking of these controls, techniques have been developed to improve measurement and modelling of permeability variability. These approaches can help improve the predictive modelling capability of reservoir performance.

Application of Cyclic Steam Stimulation on XYZ Formation in Sultanate of Oman

2016 ◽  
Author(s):  
Mohammed Al Raqmi ◽  
Hassan Al Saadi ◽  
Muhammad Mirza ◽  
Shihab Said Al Bahlouli ◽  
M. Aidil Arham ◽  
...  
Keyword(s):  
Sultanate Of Oman ◽  
Cyclic Steam Stimulation ◽  
Steam Stimulation

First Successful Autonomous ICD Pilot for GOR Management Across ADNOC Offshore

2021 ◽  
Author(s):  
Fazeel Ahmad ◽  
Zohaib Channa ◽  
Fahad Al Hosni ◽  
Salman Farhan Nofal ◽  
Ziad Talat Libdi ◽  
...  
Keyword(s):  
Oil Production ◽  
Pilot Project ◽  
Gas Production ◽  
Simulation Software ◽  
Production Performance ◽  
Production Operation ◽  
Open Hole ◽  
Early Production ◽  
Horizontal Wellbore ◽  
Selection Factors

Abstract The paper discusses the pilot project in ADNOC Offshore to assess the Autonomous Inflow Control Device (AICD) technology as an effective solution for increasing oil production over the life of the field. High rate of water and gas production in horizontal wells is one of the key problems from the commencement of operation due to the high cost of produced water and gas treatment including several other factors. Early Gas breakthrough in wells can result in shut-in to conserve reservoir energy and to meet the set GOR guidelines. The pilot well was shut-in due to high GOR resulted from the gas breakthrough. A pilot project was implemented to evaluate the ability of autonomous inflow control technology to manage gas break through early in the life of the well spanned across horizontal wellbore. And also to balance the production influx profile across the entire lateral length and to compensate for the permeability variation and therefore the productivity of each zone. Each compartment in the pilot well was equipped with AICD Screens and Swell-able Packers across horizontal open hole wellbore to evaluate oil production and defer gas breakthrough. Some AICDs were equipped with treatment valve for the compartments that needed acid simulation to enhance the effectiveness of the zone. The selection factors for installing number of production valves in the pilot well per each AICD was based on reservoir and field data. Pre-modeling of the horizontal wellbore section with AICD was performed using commercial simulation software (NETool). After the first pilot was completed, a detailed technical analysis was conducted and based on the early production results from the pilot well showed that AICD completions effectively managed gas production by delaying the gas break through and restricting gas inflow from the reservoir with significant GOR reduction ±40% compared to baseline production performance data from the open hole without AICD thus increasing oil production. The pilot well performed positively to the AICD completion allowing to produce healthy oil and meeting the guidelines. The early production results are in line with NETool simulation modelling, thereby increasing assurance in the methods employed in designing the AICD completion for the well and candidate selection. This paper discusses the successful AICD completion installation and production operation in pilot well in ADNOC Offshore to manage GOR and produced the well with healthy oil under the set guidelines. This will enable to re-activate wells shut-in due to GOR constraint to help meeting the sustainable field production target.

Numerical Simulation of Thermal Solvent Replacing Steam under Steam Assisted Gravity Drainage SAGD Process

2010 ◽  
Author(s):  
Weiqiang Li ◽  
Daulat D. Mamora
Keyword(s):  
High Temperature ◽  
Oil Recovery ◽  
Oil Sands ◽  
Steam Injection ◽  
Thermal Recovery ◽  
Production Performance ◽  
Gravity Drainage ◽  
Steam Assisted Gravity Drainage ◽  
Recovery Technique ◽  
Simulation Results

Abstract Steam Assisted Gravity Drainage (SAGD) is one successful thermal recovery technique applied in the Athabasca oil sands in Canada to produce the very viscous bitumen. Water for SAGD is limited in supply and expensive to treat and to generate steam. Consequently, we conducted a study into injecting high-temperature solvent instead of steam to recover Athabasca oil. In this study, hexane (C6) coinjection at condensing condition is simulated using CMG STARS to analyze the drainage mechanism inside the vapor-solvent chamber. The production performance is compared with an equivalent steam injection case based on the same Athabasca reservoir condition. Simulation results show that C6 is vaporized and transported into the vapor-solvent chamber. At the condensing condition, high temperature C6 reduces the viscosity of the bitumen more efficiently than steam and can displace out all the original oil. The oil production rate with C6 injection is about 1.5 to 2 times that of steam injection with oil recovery factor of about 100% oil initially-in-place. Most of the injected C6 can be recycled from the reservoir and from the produced oil, thus significantly reduce the solvent cost. Results of our study indicate that high-temperature solvent injection appears feasible although further technical and economic evaluation of the process is required.

A Physics-Based Proxy for Surface and Subsurface Coupled Simulation Models

2021 ◽  
Author(s):  
Changdong Yang ◽  
Jincong He ◽  
Song Du ◽  
Zhenzhen Wang ◽  
Tsubasa Onishi ◽  
...  
Keyword(s):  
Network Model ◽  
Reservoir Simulation ◽  
Coupled Model ◽  
Simulation Models ◽  
Production Performance ◽  
Proxy Model ◽  
Surface Network ◽  
Run Time ◽  
Multi Phase ◽  
Subsurface Reservoir

Abstract Full-physics subsurface simulation models coupled with surface network can be computationally expensive. In this paper, we propose a physics-based subsurface model proxy that significantly reduces the run-time of the coupled model to enable rapid decision-making for reservoir management. In the coupled model the subsurface reservoir simulator generates well inflow performance relationship (IPR) curves which are used by the surface network model to determine well rates that satisfy surface constraints. In the proposed proxy model, the CPU intensive reservoir simulation is replaced with an IPR database constructed from a data pool of one or multiple simulation runs. The IPR database captures well performance that represents subsurface reservoir dynamics. The proxy model can then be used to predict the production performance of new scenarios – for example new drilling sequence – by intelligently looking up the appropriate IPR curves for oil, gas and water phases for each well and solving it with the surface network. All necessary operational events in the surface network and field management logic (such as facility constraints, well conditional shut-in, and group guide rate balancing) for the full-coupled model can be implemented and honored. In the proposed proxy model, while the reservoir simulation component is eliminated for efficiency. The entirety of the surface network model is retained, which offers certain advantages. It is particularly suitable for investigating the impact of different surface operations, such as maintenance schedule and production routing changes, with the aim of minimizing production capacity off-line due to maintenance. Replacing the computationally intensive subsurface simulation with the appropriate IPR significantly improves the run time of the coupled model while preserving the essential physics of the reservoir. The accuracy depends on the difference between the scenarios that the proxy is trained on and the scenarios being evaluated. Initial testing with a complex reservoir with more than 300 wells showed the accuracy of the proxy model to be more than 95%. The computation speedup could be an order of magnitude, depending largely on complexity of the surface network model. Prior work exists in the literature that uses decline curves to replicate subsurface model performance. The use of the multi-phase IPR database and the intelligent lookup mechanism in the proposed method allows it to be more accurate and flexible in handling complexities such as multi-phase flow and interference in the surface network.

State-of-the-Art of Thermal Recovery Models

1981 ◽  
Vol 103 (4) ◽  
pp. 296-300
Author(s):  
S. M. Farouq Ali ◽  
J. Ferrer
Keyword(s):  
Oil Recovery ◽  
Input Data ◽  
State Of The Art ◽  
Front Tracking ◽  
Steam Injection ◽  
Thermal Recovery ◽  
In Situ Combustion ◽  
Cyclic Steam Stimulation ◽  
Recovery Models

Thermal recovery models for oil recovery consist of steam injection and in-situ combustion simulators. At the present time, steam injection simulators have been developed to a point where it is possible to reliably simulate portions of a fieldwide flood. Cyclic steam stimulation simulation still entails a number of questionable assumptions. Formation parting cannot be simulated in either case. In-situ combustion simulators lack the capability for front tracking. Even though the models are rather sophisticated, process mechanism description and input data are inadequate.

Integrated Characterization of Hydraulically Fractured Shale-Gas Reservoirs—Production History Matching

2015 ◽  
Vol 18 (04) ◽  
pp. 481-494 ◽  
Author(s):  
Siavash Nejadi ◽  
Juliana Y. Leung ◽  
Japan J. Trivedi ◽  
Claudio Virues
Keyword(s):  
Shale Gas ◽  
Hydraulic Fracture ◽  
History Matching ◽  
Flow Simulation ◽  
Simulation Models ◽  
Model Parameters ◽  
Fracture Parameters ◽  
Production History ◽  
Dfn Model

Summary Advancements in horizontal-well drilling and multistage hydraulic fracturing have enabled economically viable gas production from tight formations. Reservoir-simulation models play an important role in the production forecasting and field-development planning. To enhance their predictive capabilities and to capture the uncertainties in model parameters, one should calibrate stochastic reservoir models to both geologic and flow observations. In this paper, a novel approach to characterization and history matching of hydrocarbon production from a hydraulic-fractured shale is presented. This new methodology includes generating multiple discrete-fracture-network (DFN) models, upscaling the models for numerical multiphase-flow simulation, and updating the DFN-model parameters with dynamic-flow responses. First, measurements from hydraulic-fracture treatment, petrophysical interpretation, and in-situ stress data are used to estimate the initial probability distribution of hydraulic-fracture and induced-microfracture parameters, and multiple initial DFN models are generated. Next, the DFN models are upscaled into an equivalent continuum dual-porosity model with analytical techniques. The upscaled models are subjected to the flow simulation, and their production performances are compared with the actual responses. Finally, an assisted-history-matching algorithm is implemented to assess the uncertainties of the DFN-model parameters. Hydraulic-fracture parameters including half-length and transmissivity are updated, and the length, transmissivity, intensity, and spatial distribution of the induced fractures are also estimated. The proposed methodology is applied to facilitate characterization of fracture parameters of a multifractured shale-gas well in the Horn River basin. Fracture parameters and stimulated reservoir volume (SRV) derived from the updated DFN models are in agreement with estimates from microseismic interpretation and rate-transient analysis. The key advantage of this integrated assisted-history-matching approach is that uncertainties in fracture parameters are represented by the multiple equally probable DFN models and their upscaled flow-simulation models, which honor the hard data and match the dynamic production history. This work highlights the significance of uncertainties in SRV and hydraulic-fracture parameters. It also provides insight into the value of microseismic data when integrated into a rigorous production-history-matching work flow.

Uncertainty Analysis in the Production History Matching by Using Proxies as Reservoir Simulators

2012 ◽  
Author(s):  
Paulo Camargo Silva ◽  
Virgílio José Martins Ferreira Filho
Keyword(s):  
Probability Density ◽  
Reservoir Simulation ◽  
History Matching ◽  
Simulation Models ◽  
Difficult Problem ◽  
Probability Density Functions ◽  
Density Functions ◽  
Production History ◽  
Definition Of ◽  
Reservoir Simulator

In the recent literature of the production history matching the problem of non-uniqueness of reservoir simulation models has been considered a difficult problem. Complex workflows have been proposed to solve the problem. However, the reduction of uncertainty can only be done with the definition of Probability Density Functions that are highly costly. In this article we introduce a methodology to reduce uncertainty in the history matching using techniques of Monte Carlo performed on proxies as Reservoir Simulator. This methodology is able to compare different Probability Density Functions for different reservoir simulation models to define among the models which simulation model can provide more appropriate matching.

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