Khare, Sameer (Cairn Oil & Gas vertical of Vedanta Limited) | Baid, Rahul (Cairn Oil & Gas vertical of Vedanta Limited) | Prusty, Jyotsna (Cairn Oil & Gas vertical of Vedanta Limited) | Agrawal, Nitesh (Cairn Oil & Gas vertical of Vedanta Limited) | Gupta, Abhishek Kumar (Cairn Oil & Gas vertical of Vedanta Limited)
The objective of the paper is to present the methodology adopted for dual artificial system modeling in Aishwariya field– an onshore oil field located in prolific Barmer Basin, India. This paper presents a conceptual and feasibility study of combination of Jet pump (JP) and Electrical Submersible Pump (ESP) together as means of artificial lift for production enhancement in a well. It discusses the workflow to model a well producing on dual artificial lift (ESP producing in combination with Jet-Pump) via industry standard software and demonstrates the same with a successful case study.
Requirement of ESP change outs to restore/enhance well production in cases such as undersized pumps, pump head degradation requires an expensive work-over. However, an option for secondary additional lift (JP) installation along with primary lift (ESP) in completion system can eliminate the costly wok-over requirement if both lifts can operate simultaneously.
The procedure to model the dual artificial lift (JP and ESP) has two major components: a) Psuedo IPR at ESP discharge node and b) Standard JP modeling using pseudo IPR. Pseudo IPR is generated by modifying well specific IPR using ESP pump curve for a specific frequency. The down-hole ESP pump intake & discharge pressure sensors help calibrate the model accurately for further prediction.
The existing completion in the Aishwariya field is ESP completion with the option of JP installation in cases of ESP failures as contingency. Moreover, jet pump can be installed using slick line with minimum well downtime (∼ 6 hrs). Therefore, installing and operating the Jet pump above a running ESP will not only increase the drawdown but will result in production enhancement with minimal cost.
Mund, Bineet (Cairn India Ltd.) | Das, Amlan (Cairn India Ltd.) | Sharda, Ruchika (Cairn India Ltd.) | Bhat, Sudeep (Cairn India Ltd.) | Kumar, Ritesh (Cairn India Ltd.) | Gupta, Abhishek Kumar (Cairn India Ltd.) | Shankar, Pranay (Cairn India Ltd.)
The Raageshwari Deep Gas (RDG) Field, situated in the southern part of Barmer Basin, is a tight gascondensate reservoir comprising of Volcanics with basic lava flows (basalts) and stacked silicic pyroclastic flows (felsic) interbedded with basalts, and overlying clastic Fatehgarh Formation. The field is currently being developed using deviated wells with multi-stage hydraulic fracturing. The volcanic rocks pose a significant challenge in reservoir zone identification and trend prediction. Variability in mineralogy, lithofacies, thickness of reservoir subunits and areal distributions of pores/vesicles and fractures results in marked reservoir heterogeneity. This paper demonstrates a comprehensive facies characterization for pay zone identification, building a robust reservoir model and execution of multistage hydro-fracturing.
The facies characterization methodology integrates cores, mudlogs (gas shows and chromatographs), wireline logs, hydraulic fracturing and production data. Conventional (sand-shale) petrophysical workflows are not applicable to volcanic rocks that are fundamentally different in nature. Hence a new unconventional work flow was established and validated in pilot wells. It was evident that the key parameter to address would be permeability given the tight nature of the formation (micro-pores). An initial facies classification was conceptualized integrating basic suite of logs and core data. New learnings on well performance behavior were assimilated with NMR log data in further refining the facies model. Higher gas counts and higher productivity was found to be associated with higher NMR bins indicative of larger pores and hence better facies.
The pay zones identified based on refined facies model helped in optimizing hydraulic fracturing of around 100 zones in 15 wells in recently concluded Hydro-frac campaign. The pin pointing of better producible zones in an approximately 700 m thick volcanic package facilitated reduction in operational costs. Multiple perforations (clusters) were combined in each fracturing stage; injectivity of individual cluster was checked during mini-frac and post fracture temperature analysis resulting in an optimized hydro-frac job. Production logging was carried out to confirm contribution from stimulated intervals. It was observed that almost all fractured intervals were contributing to production validating the petrophysical work. Improved facies classification was also built into the reservoir model thus improving the property distribution and reservoir predictability away from the wellbore. This study facilitated in building a robust history matched reservoir simulation model for realistic production forecasting.
This case study from an unconventional volcanic reservoir emphasizes the importance of integrating different datasets, in unraveling reservoir complexity leading to increased confidence in effective reservoir management. The volcanic reservoirs pose a huge technical challenge for sustained production performance and reservoir management; calling for continuous upgrading of the facies model by aggregating data from hydro-fracturing and newly drilled wells.
Mund, Bineet (Cairn India Ltd.) | Sharda, Ruchika (Cairn India Ltd.) | Das, Amlan (Cairn India Ltd.) | Somasundaram, Sreedurga (Cairn India Ltd.) | Bhat, Sudeep (Cairn India Ltd.) | Sabharwal, Varad (Cairn India Ltd.) | Gupta, Abhishek Kumar (Cairn India Ltd.) | Shankar, Pranay (Cairn India Ltd.)
Raageshwari Deep Gas (RDG) Field in the Southern part of Barmer Basin is a tight gas-condensate reservoir composed of a thick volcanic unit overlain by volcanogenically-derived clastic Fatehgarh formation. This tight reservoir hosts significant gas reserves and is being successfully exploited with the implementation of multi-stage hydraulic fracturing. For optimum hydraulic fracture stimulation, a clear understanding of the geomechanical properties of the reservoir and its seamless integration with petrophysical interpretation is of paramount importance to achieving long-term sustainable well performance. The key geomechanical factors in hydraulic fracturing of deep volcanic reservoirs form a niche subject as opposed to the widely published unconventional shale plays. This paper illustrates the workflow developed for construction of 1D-Geomechanical model in tight volcanics and its application for selecting perforation intervals and designing of frac jobs; its validation through diagnostic fluid injection, execution of hydraulic fracturing jobs and associated challenges.
The one dimensional Geomechanical model integrates basic petrophysical logs, dipole sonic data, rock mechanical tests on core, processed image log data with break out analysis, regional tectonic history, existing natural fracture evidences and drilling data. Most importantly, the model is calibrated with field test data such as diagnostic fluid injectivity test (DFIT), step rate test (SRT) and mini-frac data. The workflow involves estimation of rock mechanical properties (Young's modulus, Poisson's ratio, uniaxial compressive strength) based on logs and calibration with core data and documented analogues. The next step is modelling of stresses in the field for identification of current stress regime. Integration of failure models with wellbore image data provides the understanding of maximum horizontal stress. Basic log data is used for estimation of over burden and pore pressure. Calibration of pore pressure is carried out from the DFIT data. The third step involves the assimilation of rock strength model with stress model to estimate minimum horizontal stress. In a geologically complex setting with multiple histories of tilting and faulting, tectonics plays an important role in the existing stresses. All these variables are captured and validated with field test data to construct a useful geomechanical model.
As part of the recently concluded hydraulic-fracturing campaign, the 1D-Geomechanical model was successfully applied to identify approximately 125 fracture stages in 20 wells for multi-cluster hydro-fracturing in the field. An effective geomechanical model, along with petrophysical interpretation has proved to be helpful in enhancing recovery, improving frac success rate and ultimately, reducing cost on operations. The approach emphasizes the importance of continuous update of the model to deal with variation within the field area and heterogeneity in volcanic rocks.
Abdelaziz, Sherif (Halliburton) | Leem, Junghun (Halliburton) | Praptono, Andri Setyanto (Halliburton) | Shankar, Pranay (Cairn India Limited) | Mund, Bineet (Cairn India Limited) | Gupta, Abhishek Kumar (Cairn India Limited) | Goyal, Rajat (Cairn India Limited) | Sidharth, Punj (Cairn India Limited)
A tight-gas reservoir commonly refers to a low-permeability reservoir that mostly produces natural gas. Irrespective of the reservoir rock type (e.g. sandstone, shales, coal seams or volcanics), they all have one thing in common—these reservoirs cannot be produced at economic rates without an effective hydraulic fracturing treatment.
In conventional reservoirs, rock flow capacity is usually sufficient to allow for hydrocarbons flow; therefore, hydraulic fracturing is broadly considered as a remedial technique to improve the productivity of suboptimal producing wells. In this study, fracturing was not originally considered in the primary drilling and completion planning phases, which in many cases limited the effectiveness of fracturing treatments because of challenges resulting from the well architecture, trajectory, azimuthal orientation with respect to dominant stress regimes, and other factors. As the importance of unconventional resources for hydrocarbon production has increased dramatically during the past decade and more attention and efforts are focused globally to explore these reserves, the demand for hydraulic fracturing techniques to prove the economic profitability of these resources has in turn tremendously increased. This has created a paradigm shift, as operators are beginning to recognize that they need to drill and complete wells for hydraulic fracturing to maximize the return on their assets. Therefore, hydraulic fracturing has gained an advanced position in the planning phase of unconventional assets.
Volcanic formations are one of the rarer rock types with the potential for accumulations of hydrocarbons that can produce economically. This rarity has resulted in a lack of understanding across the industry on the nature of these reservoirs and how to successfully turn them into lucrative assets. Because of the tight nature of these formations, optimal hydraulic fracturing strategies are intrinsically necessary for economic production. Without a thorough and integrated understanding of the petrophysical and geomechanical properties of these formations, it will be difficult to interpret the fracture growth behavior and its inherent effect on fracture flow capacity in the production phase.
Raageshwari Deep Gas Field, India is a low permeability (0.01-1md), medium CGR gas condensate reservoir. The pay-zone consists of a poorly sorted sandstone interval on top of stacked succession of thick lava flow cycles of volcanic origin. The field is developed with vertical wells and multi-stage hydraulic fractures. Developing a tight heterogeneous system comes with its own set of challenges – reservoir characterization and pay identification, fluid distribution, well placement, frac placement with optimum parameters, interconnected volumes, per well recovery, etc. This paper highlights our approach to mitigate various uncertainties to accurately predict field performance.
An extensive data acquisition plan coupled with 4 years of production history played a crucial role in identifying the correct solution set. Extended well testing was carried out for different wells during the appraisal phase. Pressure transient (PTA) data acquired during this period helped in estimating the "KH" of the various layers which was correlated with the log derived permeability and hence validating the petrophysical and geo-mechanical model. Similarly, other core and drilling data were incorporated into the model for proper reservoir characterization and pay identification. As more wells were drilled and brought on production, sufficiently long PTA was impossible. However, massive hydraulic fracturing campaign provided ample opportunity to conduct DFIT (diagnostic fracture injection test) for estimating the reservoir parameters as well as validate the model. Variation in fluid distribution across the section was expected as production data confirmed areal and vertical variation in CGR. Multiple samples were captured from different wells and a PVT model was created which justified the fluid produced. Application of Digital Oilfield ensured the continuous production data which was analyzed via RTA for guidance on "Per Well Recovery". This was integrated with traditional PTA, time-lapsed production log, core analysis and DFITs.
Such a complex system is best resolved using individual well analysis. A comprehensive workflow was created which ensured data acquired from all the individual wells were integrated and accordingly the petrophysical and geo-mechanical models were updated. The workflow permitted us to reduce our uncertainty on the key parameters of pay identification, frac optimization and Well Spacing. This improved our perspective of the field, and permitted us to optimize our field development, which is robust despite market uncertainties.
Few innovative ideas were used in our design for data acquisition to minimize the time constraint – such as extended DFITs, use of well-head pressure for PTA using an accurate well-bore model, time-lapsed flowing pressure and PLT data to study the effects of changing productivity etc. These innovations helped us move down the uncertainty ladder quickly with a high degree of confidence.
Geological sequestration of CO2 in deep saline reservoirs is one of the ways to reduce its continuous emission into the atmosphere to mitigate the greenhouse effect. The selection among prospective saline reservoirs can be expedited by developing some analytical correlations which can be used in place of reservoir simulation study for each and every saline reservoir. Such correlations can reduce the cost and time for commissioning a geological site for CO2 sequestration.
The efficiency of a CO2 sequestration operation depends on risks associated with storage, several of which can be estimated by i) the time the plume takes to reach the top seal; ii) maximum lateral extent of the plume and iii) the percentage of mobile CO2 present at any time. A database has been created from a large number of compositional reservoir simulations for different reservoir parameters including porosity, permeability, permeability anisotropy, reservoir depth, thickness, dip and perforation interval. We use a dimensionless ratio of gravity to viscous forces to formulate different correlations with the factors that contribute to sequestration efficiency. We update a previously reported correlation for time to hit the top seal and develop a new correlation for the maximum lateral extent of the plume using a newly created database for different reservoir and operating properties. A correlation for percentage of mobile CO2 during the buoyancy dominated post injection period is also developed.
We find that normalizing the maximum lateral extent by a characteristic length yields a reasonable correlation with the gravity number. This characteristic length is determined as the maximum lateral distance traveled by plume at any time assuming constant sand face velocity. The correlation confirms that low gravity number allows the plume to travel laterally due to high viscous forces while a high gravity number allows it to move faster in vertical direction due to strong gravity forces. The change in mobile CO2 after injection ends also correlates well with gravity number. We normalize the change in mobile CO2 fraction (or, equivalently, the change in trapped CO2 fraction) after the end of injection by a characteristic CO2 saturation. The characteristic saturation is obtained by considering the volume filled by vertical, buoyancy-driven movement through the area associated with the maximum plume extent.
The correlations reproduce almost all simulation results within a factor of two, and this is adequate for rapid ranking or screening of prospective storage reservoirs.
Copyright 2006, Society of Petroleum Engineers This paper was prepared for presentation at the 2006 SPE Western Regional/AAPG Pacific Section/GSA Cordilleran Section Joint Meeting held in Anchorage, Alaska, U.S.A., 8-10 May 2006. This paper was selected for presentation by an SPE Program Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the Society of Petroleum Engineers and are subject to correction by the author(s). The material, as presented, does not necessarily reflect any position of the Society of Petroleum Engineers, its officers, or members. Papers presented at SPE meetings are subject to publication review by Editorial Committees of the Society of Petroleum Engineers. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of the Society of Petroleum Engineers is prohibited.