Lack of reliable sealing materials with temperature rating over 600 °F (316°C) for downhole sealing and zone isolation applications in high temperature wells such as steam injection wells is a big material technology gap and concern for oil and gas industry. Traditionally, elastomers are the material chosen for downhole sealing applications. But this type of organic materials is prone to decompose when temperature approach 600°F (316°C) and even lower in wellbore fluids. Metal to metal seal may have the temperature tolerance, but lacks enough elasticity to provide reliable seal in downhole conditions. This paper will introduce a newly developed elastic carbon composite (ECC) and its use as an ultrahigh temperature packer element under extreme temperature conditions such as a steam injection well.
Tests show that the elastic carbon composite material has excellent thermal stability over 1000°F (538°C) and strong corrosion resistant to most downhole fluids, including hydrocarbons, brines, acids, etc. More importantly, it has also displayed improved mechanical strength (up to 15 KSI [103MPa]) and elasticity (6%). In addition, reasonable wear resistance observed from this carbon composite material proves it suitable for heavy oil recovery with high sand production. This new sealing material was fabricated into thermal packer elements which delivered superior sealing performance at high different pressure above 600 °F (316°C) and thermal shock cycles between 600 °F (316°C) and room temperature.
In this presentation, we will discuss the material design of this novel elastic carbon composite, the superior material properties compared to elastomeric seal materials, and the reliable performance of the ECC packer elements. The elastic carbon composite fills the technical gap of sealing material with temperature rating over 600 °F (316°C) and provides reliable solution to heavy oil recovery in the oil and gas industry.
Coiled tubing (CT) is widely used during sand cleanout applications for its multiple benefits, such as speed, cost effectiveness, minimum reaction time, efficient operations, the ability to perform live intervention cleanouts, etc. However, these benefits are difficult to achieve in complex, offshore, high-pressure/high-temperature (HP/HT), or big bore wells because of various operational constraints, such as weight, dimensions, wellbore trajectory, and completion design, resulting in increased expenditures and operation time for workover activities.
This paper describes how these constraints were eliminated using a synergy of an innovative fluid system and engineering to perform a challenging, balanced sand cleanout treatment using 1.75-in. 5800 m long CT in ~500 m of a 7-in. 35-lbf casing section executed in a 5300-m deep HP/HT well.
The deep HP/HT well had a minimum restriction of 2.56-in. in the upper completion limits, requiring large-diameter CT strings and a bottomhole assembly (BHA). Feasibility studies for use of a 1.75-in. CT vs. 2-in. CT string were performed, resulting in the selection of the 1.75-in. string. Another challenge was executing sand cleanout in a balanced condition, resulting in the selection of a saturated 13.1-lbm/gal potassium-formate (K-formate) brine. The combination of all three major constraints, a) 500-m long 7-in. section, b) use of 1.75-in. CT string, and c) use of saturated brine, made the cleanout design challenging, as sand cleanout with CT requires circulation rates, net particle rise velocity, friction pressures, viscosity, and fluid properties within the design envelope. However, the inversely proportional nature of such treatments means tuning of one property would decrease the operational feasibility of other properties.
Based on results of several tests, a customized fluid recipe was designed containing a gelling agent that can become hydrated in saturated brine and remain stable at high temperatures. A compatible friction reducing agent was used to help reduce pumping friction to attain the desired annular fluid rate and velocity. A field test was performed with the designed fluid at surface with a CT string that was to be used for operations, confirming the effectiveness of the fluid recipe.
Using downhole turbulence created by the tool, along with the custom-designed recipe in combination with wiper trips, the necessary design parameters were achieved for the cleanout operation, resulting in a) effective sand cleanout with ~98% efficiency, b) reduced operating hours, c) cost savings on workover operations, d) safer operation by keeping the well in a balanced condition, and e) a contingency action in place for screenout during fracturing treatments.
The procedure described in this paper, along with lesson learned, can be applied in similar applications to help optimize results and overcome related challenges.
Timely and detailed evaluation of in-situ hydrocarbon flow properties such as oil density and viscosity is critical for successful development of heavy oil reservoirs. The prediction of fluid properties requires comprehensive integration of advanced downhole measurements such as nuclear magnetic resonance (NMR) logging, formation pressure, and mobility measurements, as well as fluid sampling.
The reservoir rock presented in this paper is an unconsolidated Miocene formation comprising complex lithologies including clastics and carbonates. The reservoir fluids are hydrocarbons with significant spatial variations in viscosity ranging from (60-300 cP) to fully solid (tar). Well testing and downhole fluid sampling in this formation are hindered by low oil mobility, unconsolidated formation that generates sand production, emulsion generation, and very low formation pressure.
We present a two-pronged log evaluation workflow to identify sweet spots and to predict fluid properties within the zones of interest. First, the presence of "missing NMR porosity" and "excess bound fluid" is estimated by comparing the NMR total and bound fluid porosity with the conventional total porosity and uninvaded water-filled porosity logs, respectively. Secondly, two-dimensional NMR diffusivity vs. T2 NMR analysis is performed in prospective zones where lighter and, possibly, producible hydrocarbons are detected. The separation of oil and water signals provides a resistivity-independent estimation of the shallow water saturation. Additionally, we correlated the position of the NMR oil signal with oil-sample viscosity values. The readily available log-based viscosity greatly improves the efficiency of the formation and well-testing job.
We successfully sampled high viscosity hydrocarbon fluids by utilizing either oval pad or straddle packer. The customized tool designed for sampling aided gravitational segregation of clean hydrocarbons from the water-based mud filtrate and emulsion; and therefore providing representative reservoir fluid samples based on downhole fluid analyzers.
Oil price is a determinant factor in many economic equations. The consistent growth of oil demand indicates the importance of petroleum products in the economic growth of both developing and developed countries. The new market conditions after the introduction of the shale oil and the extent of its influence on determining the oil price indicates a requirement for new oil market models that include new parameters. In this paper, based on the system dynamics methodology, we provide an updated model of the supply and demand of the oil market to explain the market trends. Our model provides the causal relations between the major components of the market including the determinants of the supply and demand. We divide the supply into the OPEC, non-OPEC and US producers. Further, we have extracted the supply of Iran, Saudi Arabia, Libya, Venezuela, and Iraq in the OPEC, and Russia and Syria in the non-OPEC categories in order to be able to further detail the effects of specific events that influenced their corresponding productions. We also provide a detailed case study of the major market events after 2010 that have had consequences on the oil market. Finally, we train the model with the 2014 and 2015 data and simulate and validate the model for 2016 to support our model's performance.
Outputs from geological and geophysical applications are the major drivers for upstream prospect generation and field development. The current generation of applications can quickly produce a massive amount of intermediate data based on the iterative and interactive workflows. One major challenge for large organizations, with many disparate software systems and a large user base, is maintaining a clean and optimized data environment. Data management plays a key role in the delivery of accurate and efficient interpretation results to improve the decision making and exploration success. This case study shares the authors’ experience in leading corporate and project-based geoscience data management activities for several industry-leading applications.
The first activity was the data cleaning, standardization, and consolidation of over a 100 repositories of multiuser project-based application databases that had accumulated over 20 years. The objective for each step (data cleaning, standardization, and consolidation) was clearly defined and the processes have been implemented using best technologies. Automatic procedures have been implemented to optimize the master and interpretation data. In addition, this paper addresses the application of knowledge management methodologies, to transform existing geoscience interpretation workflows into a knowledge-based asset management system. We present the business drivers for each activity, challenges faced, and the approach adopted to resolve those challenges.
During the data management activity, many of the project databases need to remain active for ongoing well planning, monitoring, and geosteering, which make data management more challenging. New naming conventions were also established and enforced. These provided a larger than expected benefit to the users, in terms of data accuracy and availability. One sizeable operational database achieved around 55% clean up from projects’ archival and deletion. It it because projects are either not active anymore or merged with other projects. Geophysical interpretation has become an iterative, interactive, and resource intensive process. It generates massive amounts of maps and volume-based attribute data, resulting in significantly increased storage utilization and data complexity. The major challenges were to identify and extract the best available interpretation version, streamline the data flow, and leverage existing corporate knowledge. All challenges were tackled successfully, bringing a huge benefit to the organization. The creation of new processes, awareness, standards enforcement, and automation guided geoscientists toward the best data management practices. Benefits in reducing operational costs and improving productivity have been realized.
Innovative approaches utilized in our activities include knowledge management methodologies, automatic procedures implementation for data management and optimization. In addition, a continuous reporting mechanism was established to assure complete control and monitoring of data growth. This paper also provides a roadmap that can be applied to similar data management activities in the geoscience domain. Data management has been transformed into a continuous process, rather than a one-time task.
Reddy, S. S. (Oil and Natural Gas Ltd) | Anjaneyulu, J. V. (Oil and Natural Gas Ltd) | Lal, Abhay Kumar (Oil and Natural Gas Ltd) | Rao, E. J. (Oil and Natural Gas Ltd) | C H, Ramakrishna (Oil and Natural Gas Ltd) | Talreja, Rahul (Schlumberger) | Bahuguna, Somesh (Schlumberger) | Zacharia, Joseph (Schlumberger) | Chatterjee, Chandreyi (Schlumberger) | Basu, Jayanta (Schlumberger)
Malleswaram field in Krishna-Godavari (KG) basin has proven gas reserves in the late Cretaceous Nandigama formation. Many drilling challenges were faced, including losses, tight hole, and stuck pipe in the Raghavapuram and Nandigama formations overlying the reservoir interval. This study was conducted to provide a solution for drilling optimization by mitigating drilling-related nonproductive time (NPT). Integration of acoustic and geochemical data for geomechanics study provided a new insight into cause of overpressure and need for revamping of casing policy to significantly improve wellbore stability, mitigate risks, and ensure future drilling success. Generated stress models can be used to optimize hydraulic fracturing in these reservoirs. A completion quality based on stress model indicates the need for multistage fracturing due to the presence of stress barriers inside sand units in Nandigama formation.
Spyrou, Charidimos E. (Schlumberger) | La Rosa, Andres Pieve (Schlumberger) | Khataniar, Sanjoy K. (Schlumberger) | Uzoechina, Frank (Wintershall Holding GmbH) | Awemo, Kilian N. (DEA Deutsche Erdoel AG)
A pattern flood management method based on a streamline simulator was developed to support waterflood designs. The methodology was applied on a structurally complex oil field in the North German basin. Studies are being conducted to understand the potential for extending the current waterflood in this oil field. The objective of this study was to investigate if a conventional simulation-based waterflood design could be enhanced using streamline simulation.
An alternative to using streamline simulation could be the post-processing of streamlines based on outputs of a full-field finite difference (FD) simulation model. However, there are limitations to this approach, including robustness and time considerations, especially when multiple runs with field-scale reservoir models are required. The streamline simulator contains a pattern flood management algorithm designed for optimizing the performance of waterfloods using multiple value criteria. The algorithm continuously balances patterns during forecasting runs converging to optimal injection and production rates while honoring well and field production constraints. A unique set of pattern performance diagnostics are ancillary products, for example pattern efficiencies and leakage fractions.
The full-field FD dynamic model of the aforementioned oil field was adapted for the streamline simulator. Both simulation models delivered similar results at the field and well levels and matched historical observed data satisfactorily. The best pattern flood model converged on a rate schedule that led to a 4% increase in oil production, a 17% decrease in water production, and a 5% reduction in the water injection volumes over the best performance achieved using a conventional voidage replacement strategy in the FD model. These findings were validated by executing the full-field model on a FD simulator with the recommendations from the pattern flood simulation run. The streamline simulation runs executed about seven times faster. To investigate the well count optimization potential, rigorous analyses were performed on the pattern information produced by the enhanced runs. A 12.5% reduction in well count, in terms of injectors and producers, could be achieved, and the pattern flood management algorithm converged on a rate schedule that still led to an increase of 2.3% in oil production, a 22% decrease in water production, and a 10% reduction in injection volumes.
The streamline-based simulation study proved useful in improving the existing waterflood design. Speedup in runtime allowed ample investigations and analysis within a given time period. Detailed analysis of allocated rate schedules and pattern information across numerous forecast runs gave deeper insight on the problem. The study highlighted that any well pattern has associated with it an optimal rate-scheduling strategy. Hence, the two components are important aspects of any successful waterflood design. The recommended rate schedules are model based and hence subject to uncertainty, requiring updates as additional information becomes available over time.
Polymer augmentation of waterfloods is the application of polymer flooding in a secondary mode prior to significant water injection. Polymer flooding is a mature enhanced oil recovery (EOR) technology with a distinctive advantage where an existing waterflooding infrastructure exists. In this work, we design and evaluate secondary polymer augmentation for a slightly viscous Arabian Heavy reservoir at the laboratory scale. We follow a systematic and comprehensive workflow to characterize the polymer performance and behavior to gain sufficient level of understanding for future simulation-based scale-up.
We firstly capitalize on previous long-term stability results of several polymers in similar high temperature and high salinity conditions to select a potential polymer for the current application. We characterize the polymer rheology at reservoir conditions. Then, we adopt a fractional-flow based approach for initial optimization of polymer concentration. Traditionally, rough measures such as ratios of viscosity or endpoint mobility are used to set the initial polymer concentration used in laboratory evaluation. This could lead to simulation-based optimals that are much different and hence are ill-based since they are actually outside the models domain of prediction/confidence. The adopted fractional-flow workflow addresses this limitation and minimize the number of future experimentation. The workflow uses the reservoir previously established two-phase flow functions and the polymer measured rheology as inputs while accounting for both heat and shear degradation to optimize concentrations based on polymer utilization factor as an objective function. Later, we select several core-plugs from the same well based on porosity-permeability cross plots, Winland rock-typing, and nuclear magnetic resonance (NMR) pore-throat distributions. We conduct a set of three oil-displacement experiments across three different rock types at reservoir conditions and using composites of two-plugs that have been aged for 8 weeks. Dean stark analysis followed to assure consistency of remaining oil estimates. Finally, we perform a single-phase displacement experiment to characterize the polymer in-situ rheology, injectivity, adsorption, and inaccessible pore-volume. The experiment consists of three phases (water/polymer/water) each ran until pressure stabilization and at four different injection rates. A cover tracer was co-injected with the polymer. Polymer concentrations in effluents are estimated based on total organic content (TOC) analysis and NMR spectroscopy while tracer concentrations are estimated based on gas chromatography (GC).
Fractional-flow based optimization suggested an initial target viscosity of 4 mPa.s. At this viscosity, we achieve optimal utilization for the selected polymer while accounting for the expected surface and wellbore mechanical degradation as well as the in-situ long-term thermal degradation. At those levels of degradation, this target viscosity can be achieved with an injection concentration of 5500 mg/L. In terms of recovery, all three oil displacement experiments conducted using a displacing solution of 4 mPa.s demonstrated the significant potential of polymer augmentation in terms of both recovery acceleration and enhancement at a given threshold of watercut or pore-volume. For instance, after 1 pore-volume, the incremental recovery averaged around 15% OOIC (original oil in core). Finally, the single-phase experiment conducted at the suggested injection concentration further supported the selected polymer potential from injectivity and consumption standpoints: the polymer affects a manageable residual resistance of around 3 and exhibits a reasonable dynamic adsorption of 0.28mg/g-rock.
In this study, a review of production performance of four existing horizontal producers equipped with Inflow Control Device (ICD) completions was conducted using 4-D dynamic modelling on a sandstone reservoir with high water mobility. The aim of this study was to investigate the optimum regulation degree across ICD completion i.e. the ratio of pressure drop across ICDs to the reservoir drawdown, suitable to delay water breakthrough, minimize water cut and achieve production balance.
A single wellbore model was built by populating rock and fluid properties in 3-D around the wellbore for each of the studied wells. The model was then calibrated to the measured production log flow profile and bottomhole pressure profile for the deployed ICD completion in each well. Thereafter, several ICD simulation cases were run at target rates for a production forecast of 4 years. An optimum ICD case for each well was selected on the basis of water breakthrough delay, water cut reduction and incremental oil gain.
The study results showed that there is a correlation between reservoir heterogeneity index, well productivity index (PI) and optimum regulation degree required across ICD to achieve longer water breakthrough delay and better water cut control. In general, high heterogeneity, high PI wells require higher regulation degree across ICD of close to one; medium heterogeneity, low PI require regulation degree across ICD of between 0.3 – 0.45 while low heterogeneity, low PI, require very low regulation degree of between 0.1 – 0.15. Based on study results, a new ICD design framework and correlation chart were developed. This framework was then applied to two newly drilled horizontal producers to test the applicability of the workflow in real time ICD design scenarios and positive results were achieved.
Given the significant number of ICD completions deployed yearly, this new ICD design framework would provide guidance on how much pressure drop across ICD is required during real time design for newly drilled or sidetrack wells and would ultimately ensure maximum short and long term benefits are derived from deployment of ICD completions.
Xu, Yandong (Research Instittue of Petroluem Engineering, Sinopec North-West Branch) | Pang, Wei (State Key Laboratory of Shale Oil and Gas Enrichment Mechanisms and Effective Development, Sinopec Research Instittue of Petroluem Engineering) | Li, Shuanggui (Research Instittue of Petroluem Engineering, Sinopec North-West Branch) | Zou, Ning (Research Instittue of Petroluem Engineering, Sinopec North-West Branch) | Du, Juan (State Key Laboratory of Shale Oil and Gas Enrichment Mechanisms and Effective Development, Sinopec Research Instittue of Petroluem Engineering) | Mao, Jun (State Key Laboratory of Shale Oil and Gas Enrichment Mechanisms and Effective Development, Sinopec Research Instittue of Petroluem Engineering)
Shunnan Block in North-West China is one of the toughest HPHT gas reservoirs with vertical depth over 7500 m, formation temperature over 200 and pressure gradient varying from 1.3 to nearly 2. The condition is close to temperature and pressure limit of well testing tools, therefore, the tools are hard to be sent to downhole and chances are that well testing operations usually failed. The pressure buildup data are with bad quality and needed to be converted into downhole data. Meanwhile, it's hard to diagnose accurate flow regimes and interprete because the block is typically carbonate reservoirs with porous medium including pores, natural fractures and caves.
In this paper, we reviewed the exploration wells in this block and find that interpretation by pressure buildup or transient production data can only reflect part of the formation information; therefore the two kinds of data are combined to get more accurate interpretation results. For pressure buildup interpretation, three models including dual porosity model, composite model, and dual porosity with composite model are chosen and compared. For the production data, dual porosity model with boundary is selected because the wells usually show characteristics of multiple porous medium and boundary dominated flow. Parameters interpreted from pressure buildup data are simultaneously transferred into the model for production data.
Results show that the combined interpretation by pressure buildup and production data can reduce the un-uniqueness of models as well as enhancing the accuracy of formation and wellbore parameters evaluation. The model and parameters can satisfy both pressure buildup and production data history. Although Shunnan block is considered as one greatly promising reservoir from the short period open flowing, the combined interpretations suggest very limited drainage volume. Reasons for this paradox phenomenon may be that the wells are severe contaminated by drilling fluid, or the wells were only producing gas in caves and natural fractures nearby the wells while other caves are not connected.