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.
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.
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.
An ensemble-based 4D seismic history matching case is presented. Seismic data are re-parameterized as distance to 4D anomaly front and assimilated with production data. The field is a large turbiditic system, with initial fluid pressure close to the bubble point. Production causes the pressure to fall below the bubble point, resulting in a widespread gas-exsolution. The time-lapse change in gas saturation is considered responsible for the observed negative relative changes in seismic velocity seen over the all reservoir. This study is innovative for two reasons. First, the distance-to-front parameterization is applied to the gas-phase which appears everywhere in the field, rather than coming form an injection source like in previous application of the parameterization. Second, the binarization of the simulated time-lapse anomaly is performed circumventing the use of a petroelastic model; the petroelastic model would be necessary to relate the measurements to fluid properties changes and to decide a threshold for binarizing observations and pressure. However, the effect of gas is so widespread and evident that the petroelastic model is replaced by a clustering approach based on the gas saturation change of the reservoir cells. This study shows that adding the 4D re-parameterized seismic data in addition to the production data is keeping a reasonable match with production data while constraining the overall gas distribution in the reservoir to the observed seismic data.
In a horizontal well, apparent resistivity curves often show varied separations and increased values due to the polarization horn effects near a boundary and other effects such as adjacent beds or anisotropy. The true formation resistivity (Rt) is uncertain and can be mis-interpreted. As a consequence, saturation estimates are uncertain so that the reserves cannot be accurately predicted. A full inversion can be used to derive the true Rt. However, the instability of an inversion due to the lack of measurement variation along the measured depth makes the Rt derivation very challenging.
To determine a true Rt from the logging-while-drilling (LWD) resistivity measurements, a general full inversion is usually time-consuming and needs some inputs on formation model. This paper presents an alternative approach to derive the true Rt without input of any prior information. The alternative approach uses a simple two-layer model for the removal of horn effects and derives a solution at two steps: a) inverting resistivities of the two layers at each distance away from the boundary; b) selecting a solution with specific constraints such as using statistics in a moving window and internally consistent physical constraints to make the solution more reliable. In the first step, neural networks are developed to calculate tool responses and derivatives for the savings of computation time and memory needs.
Synthetic examples show that true Rt can be recovered when the relative dip between a borehole and a layered formation is greater than 85 degrees. The examples show that bed boundaries can be reproduced with sufficient accuracy by our approach, among others to define pay zone intervals. In addition, the resolution of the method was studied with models of different layer thicknesses and is discussed in details in the paper. As an outcome, the derived true Rt reads lower in a resistive thinner layer and reads slightly higher in a conductive thinner layer. A field example from a North Sea oil field demonstrates very promising and robust Rt results from the method.
The inversion is fully automatic and can be used in real time and downhole. Physical constraints that are special to a horizontal well and better strategies make our algorithm robust and very fast.
Cao, Cheng (China University of Petroleum at Beijing and Research Institute of Shanxi Yanchang Petroleum Group Co. Ltd) | Li, Tiantai (China University of Petroleum at Beijing) | Zhao, Yongpan (Research Institute of Shanxi Yanchang Petroleum Group Co. Ltd) | Xue, Jinquan (Technology Research Center of Exploration and Development of YanChang Oil Field) | Ren, Zhongxin (Gas Storage Project Department, West-East Pipeline Company, PetroChina) | Li, Yudan (China University of Petroleum at Beijing)
In order to characterize the influence of diffusion effect, stress sensitivity, matrix shrinkage and adsorption layer on shale gas permeability, weighted coefficient is used to establishdiffusion permeability model by couple transition diffusion and Knudsen diffusion. And the effect of matrix shrink, stress sensitivity and adsorption layer are considered into shale gas permeability model. The shale gas permeability model is verified by permeability experiment result of shale core in Ordos basin and discussing the effect of each parameter. The results showed that: (1) When the weighted coefficient- Km, n and m is 7, 4 and 16 respectively, the proposed diffusion permeability highly agrees with Fick diffusion, transient diffusion and Knudsen diffusion, that can represent diffusion of the whole flow stage.(2) Under the conditions of low pressure and small pores, diffusion flow is the main control factors of shale gas transmission; and under the condition of high pressure and large pores, viscous flow mainly controlling shale gas transmission.(3) The influence of stress sensitivity and adsorption layer on shale gas permeability is bigger, and the influence of the matrix shrink can be ignored.(4) Adsorption layer have a significant impact on the shale gas permeability under the conditions of high pressure and small pores. The proposed shale gas permeability model can eliminate the deviation result from describing the shale gas diffusion only by using Knudsen diffusion model, and also can describe the shale gas transmission under a multi-physic field, and thus it is significantly enlighten the development of shale gas.
Ahmadi is a shallow carbonate reservoir consisting of two units AA and AB. These units are thin, highly faulted and irregularly-fractured. The matrix permeability of Ahmadi is very low; it ranges between 0.01 and 10 md. However, the secondary permeability is playing a big part on achieving some remarkable production figures.
The reservoir is believed to have some fractures which have been proven from image logs. These make the simulation of the reservoir quite challenging. This paper describes how fractures were incorporated in the simulation of Ahmadi where three different methodologies have been considered. These are: single porosity with seismic attributes enhancement, dual porosity dual permeability (DPDP) and virtual fracture network modeling.
In the single porosity model, the fracture properties were represented along with the matrix properties in one cell. It was done by considering some seismic attributes such as Anttrack and Anisotropy and then using the Attributes distributions to generate permeability multipliers. For the Dual Porosity Dual Permeability model where the matrix and fracture cells are different, the seismic attributes were used again but to generate a stochastic fracture network. Alternatively, the virtual fracture network model was created by having fractures intersecting each well based on some assumptions related to well spacing, fracture aperture and fracture direction.
The listed methodologies are discussed in details in this paper. It was found that the virtual fracture network approach led to fast and robust history matching results. It was also observed that Anttrack and Anisotropy seismic attributes helped to represent the fault and non-fault related fractures in both single porosity and dual porosity dual permeability models.
Yuan, Peng (Baker Hughes Incorporated) | Zhang, Hao (Baker Hughes Incorporated) | Huang, Xu (Baker Hughes Incorporated) | Han, Jiahang (Baker Hughes Incorporated) | Zhou, Quming (Baker Hughes Incorporated) | Mezzatesta, Alberto (Baker Hughes Incorporated) | Bao, Jie (Pacific Northwest National Laboratory)
Multistage hydraulic fracturing is widely applied for developing unconventional reservoirs with low permeability. The plug-and-perf method is the most commonly used staging method especially for horizontal wells. Fracturing fluids are usually pumped from the surface to create fractures after perforation clusters are established for each stage; next, proppants are placed into the fractures to keep them open. Field and experimental work have shown that proppant transport in multistage plug-and-perf completions can cause severe erosion on perforations. However, modeling proppant erosion process is still an intricate task that proves to be challenging within the industry due to complexity of the problem. In this work, proppant erosion is investigated by using computational fluid dynamics (CFD) modeling. The effects of sand particle diameter, proppant loading, fracturing fluids viscosity, slurry injection rates, and the pipe angle are analyzed to determine the rate of erosion within the perforations. Several erosion models are used and the simulation results are compared.
The numerical simulation results produced by using the proposed CFD model indicate that proppant can increase the diameter of the perforation. The unevenness of diameter increasing would further compromise the fracturing design because of one cluster accepting more fluid than its counterparts and affecting the distribution of the proppants in the cluster. The flow lines and couplings also show significant wear due to proppant erosion. The simulation results using the Oak erosion model are found to agree with the findings in the inside-casing experimental test.
The results of this study indicate that proppant erosion in multistage hydraulic fracturing can be accurately modelled when proppant properties, fracture geometry, and slurry rheology are all considered in the CFD simulation model. The simulation methodology proposed and discussed in this paper provides a better understanding of fluid and proppant behavior and proves that CFD is an effective tool for reducing the wear of perforations and pipes caused by proppant erosion and hence, optimizing hydraulic fracturing design.