California is known for being at the forefront of renewable technology adoption and greenhouse gas emissions curtailment. Even in an industry seen by many residents as archaic, oil producers are increasingly seeking out alternative sources of energy to use in operations. The high number of aging heavy oilfields, high quantity of sunshine, and state's environmental sensibilities make for an ideal proving ground for a technology that brings two divergent industries together: solar thermal enhanced oil recovery (EOR). In 2011, Berry Petroleum and solar energy provider GlassPoint started up a 300-kW thermal project at McKittrick oilfield in Kern County that ultimately produced 1 million Btus/hr of solar heat over its 5-year lifespan while reducing the field's gas consumption. That same year, Chevron Technology Ventures and BrightSource Energy launched a 29-MW thermal solar-to-steam facility as part of a 3-year pilot project at Coalinga oilfield in Fresno County.
Yang, Lei (Baker Hughes, a GE company) | Bale, Derek S. (Baker Hughes, a GE company) | Yang, Don (Baker Hughes, a GE company) | Raum, Matthew (Baker Hughes, a GE company) | Bello, Oladele (Baker Hughes, a GE company) | Failla, Roberto (Baker Hughes, a GE company) | Lerohl, David (Baker Hughes, a GE company) | Knowles, David (Shell Global Solutions US Inc) | Kwari, Andy (Shell Global Solutions US Inc) | Cannon, Matt (Shell Global Solutions US Inc) | Ye, Shuzhen (Shell Global Solutions US Inc)
The distributed nature of fiber-optic measurements such as distributed temperature sensing (DTS), distributed acoustic sensing (DAS), and distributed strain sensing (DSS) enables nearly continuous monitoring of the downhole environment in both space and time. Though continuous monitoring opens the door to a rich new set of asset management applications, it comes with its own set of challenges in terms of data transmission, management, and security. Recently, cloud-based fiber-optic data management services have been successfully introduced to the oil and gas industry as an effective way to collect, transfer, store and display distributed measurement data from the downhole environment. To maximize the value of such cloud-based data management systems, and further improve the return on investment for asset managers, the large volume of distributed sensing data collected must be converted to value in a simple and easy-to-use form, depending on different applications. Traditionally, interpretation of distributed sensing data is a manual process conducted by engineers in a post-job workflow. This paper presents the successful integration of an analytics library into the cloud-based fiber-optic data management system. This integration enables real-time, and in some cases near real-time, asset decision making. The design of the analytics architecture is open to meet the wide range of application requirements by asset managers. A few application examples of the analytics integration will be presented using real-time data streamed directly from the field.
Solórzano, Pedro (Ecopetrol, S.A.) | Ahmedt, Diana (Ecopetrol, S.A.) | Jaimes, Claudia (Ecopetrol, S.A.) | Henao, William (Ecopetrol, S.A.) | Vega, Sandra (Ecopetrol, S.A.) | Guerrero, Cindy (Ecopetrol, S.A.) | Meza, Eliana (Ecopetrol, S.A.) | León, Juan (Ecopetrol, S.A.) | Dueñas, Danuil (Ecopetrol, S.A.)
This paper presents the application of multiple selectives injection zones within a high thickness singled bed heavy oil sand. The results were compared with a single zone completion in the same sand, establishing the differences in several aspects like recovery factor, vertical distribution efficiency, operation styles and completion difficulties.
This approach is based on the application of two methods of water vertical irrigation in a heavy oil sand, first, a singled 300’ zone completion and else, a 3-4 selectives zones completion, separating the equivalent injection in spaces of 60’-100’ thickness each. To route the flow, the packers were located next to thin shale planes most as possible. The objective was use this natural inundation surfaces intentionally as vertical permeability barriers looking forward to this works as a vertical flow controllers beyond wells selectivization, means like flooding separators, inside the heart of reservoir. In injector wells 3 types of behavior profile logs were ran several times within more than two years.
The reservoir under study it is the sand T2 located at Chichimene field, at the Colombia Llanos Basin. It has 320’/250’r of gross/net thickness, physically looks like a singled bed, it is saturated with high viscosity extra heavy oil of 350 cps, it is located at 9000’ measured depth (6000 - 6800’ TVDSS) the permeability shows a broad permeability range of 5 – 10000 mD. Waterflooding was initiated by 2014, the single zone completions wells, were exposed to a 6000 bls/d rate over very high permeability layer and this produced immediate channelization in thin layers only in some weeks after initiated. Producer wells increased water cut to high values, injection rates were controlled as results of its and finally some of the injectors had to be shut in. In the other set of wells, selective applications got separate the sand by 3 or 4 zones, the reservoir sand were irrigated by the same time, at the same rate of 6000 bls/d, almost 2000 bls/d each zone, this time the trends were simply different, means, producers water cut it was low and more stable. The results shows up about 2-3% of RF by simple zone completion in opposite to 6-10% of RF with selectives completions, evidencing a better vertical irrigation.
The case study presented in this paper, it is a successful curiously application of multiple selectives completions within a single sand. This example has been tested in field, it is an effective option in order to increase recovery factor and it will reborn expectations about the use of selectives completions over thick heavy oil sands. This results definitely; it will encourage engineers to think more about mechanical conformance applications in waterflooding.
ABSTRACT: Hydraulic stimulation and production-induced permeability alteration in stress-sensitive Monterey Formation rocks require an in-depth understanding of the deformation behavior of different rock types. Here, we evaluate and compare deformation behavior of two types of clastic rocks—shale and sandstone—across nano-to-micro scales using experiments and simulations. Using core samples of shale from the Monterey Formation and tight sandstone from the Dominguez Hills in California, we conduct nanoindentation, scanning electron microscopy and particle-based simulation to understand the difference in deformation behavior of shale and sandstone under different loading-unloading conditions. We quantify Young’s modulus, hardness modulus, and stiffness of the rocks using nanoindentation data. Our work provides important insights into grain-scale deformation behavior of two different rock types commonly found in petroleum reservoirs. Understanding of grain-scale failure mechanisms can inform development of new upscaled constitutive models for usage in continuum-scale field simulations, which cannot afford to resolve the grain-scale processes due to computational cost.
Hydraulic fracturing in conjunction with directional drilling has been a game-changing technology for the development of oil and gas resources. It has unlocked vast oil and gas resources in shales and low permeability sandstones which were once considered unfit for commercial production. However, the success of hydraulic fracturing has not been uniform across different types of shales and sandstones. For example, the potential for unlocking millions of barrels of oil from Monterey Formation, California by hydraulic fracturing has been a topic of much debate (EIA, 2011; USC, 2013; EIA, 2014; USGS, 2015). Belridge diatomite, a part of Monterey Formation, has been produced successfully by increasing its low matrix permeability with hydraulic fracturing in 1970-80s. However, the Belridge Field is also well-known for production-induced subsidence and widespread casing failures (Fredrich et al., 1996). Diatomite rock is highly stress-sensitive and can experience pore collapse, reservoir compaction, and induced fracturing due to pressure depletion during production. Our lack of understanding of the geomechanical processes and properties in a geologically complex rock such as Monterey prevents us from designing successful hydraulic stimulation and pressure depletion strategies.
ABSTRACT: A multi-scenario geomechanical modeling approach is presented to investigate the potential mechanisms that lead to a series of observed well deformation incidents in the deep overburden overlying a depleting and compacting chalk reservoir in the North Sea. Complementary to the commonly pursued approach of building a full-field geomechanical model, a suite of detailed ideal geomechanical models is developed based on data and evidence driven scenarios that take into considerations fault population and juxtaposition, contrasting mechanical stratigraphy, intra-bedding contact conditions, and lateral persistence of thin stringer beds. The simulation results of extensive runs suggest that as the majority of faults in the overburden mudstones would remain stable under the pre-production stress state, however, the contrasting mechanical stratigraphy consisting of thick compliant mudstone and thin stiff carbonate stringers facilitates “domino” or “bookshelf” style intra-bedded shear slippage in response to the developing dominant shear zone around the periphery of the active compacting region. This multi-scenario approach provides new and accelerated insights into the diagnosis of compaction-induced well failure and allows mapping of competing mechanisms potentially responsible for the problem, which helps to steer further modeling efforts, and guides future data acquisition.
Despite previous industry studies [1-7] and continuing investigation and modelling efforts, there remain challenges with regards to the understanding of key mechanisms relevant to well casing damage and deformation due to reservoir compaction, subsidence and corresponding deformation of the overburden. These challenges are particularly associated with insufficient data collected outside the reservoir which inhibit diagnosis and appropriate analytical and numerical techniques that are able to replicate and predict the occurrence of well incidents. As a commonly pursued approach, full-field geomechanical models practically loaded with all available information are perceived the way to go, as reported in previous studies [1, 3, 5] and a companion publication . In this study we consider some key technical challenges in modeling the overburden deformation:
(i) Recognizing that geological faults are necessary in the understanding of well deformation in the overburden, full-field models are constrained in terms of representing the complete fault system present in the volume of interest.
(ii) The full-field model suggests that faults under the current in-situ stress states are far from being critically stressed, as opposed to initial expectation during model framing.
(iii) The effect of reefs and key mechanical layers, though introduced and assigned mechanical properties relevant to field data, do not appear to show an impact.
(iv) The coarse mesh resolution is suboptimal for geological faults and detailed mechanical stratigraphy consisting of thin layers of strong property contrast.
(v) The effect of other forms of geological discontinuities, such as lithological contacts, are completely unaccounted.
Temizel, Cenk (Aera Energy) | Salehian, Mohammad (Istanbul Technical University) | Cinar, Murat (Istanbul Technical University) | Gok, Ihsan Murat (Istanbul Technical University) | Alklih, Mohamad Y. (ADNOC)
With the advances in data-driven methods, they have become more widely-used in analysis, predictive modeling, control and optimization of several processes. Yet, as it is a relatively new area in petroleum industry with promising features, the industry overall is still skeptical on use of data-driven methods as it is a data-based solution rather than traditional physics-based solutions. In this sense, in order to shed light on the background and applications in this area, this study comparatively evaluates one of the methods used in waterflood surveillance and optimization called capacitance-resistance model illustrated on two types of mature fields with high and low-perm characteristics.
Data-driven methods serve as a robust tool to turn data into knowledge. Historical data generally has not been used in an effective way in analyzing processes due to lack of a well-organized data where there is a huge potential of turning terrabytes of data into knowledge. A capacitance-resistance model is built to identify the well connectivities between the wells and then carry that knowledge to better reservoir management through optimization of injection and production in two different sets of data.
In CRM modeling, analysis of injection/production data at associated injectors and producers reveals the connectivities and further optimization leads to optimum injection values. Steps and the methodology of building a CRM model using real data is illustrated to exemplify the whole process in a comparative way between two mature reservoirs. We introduce the concept of application of spatial constraints in terms of injection-producer maximum influence radius to accelerate and improve the solution where knowledge of radius of influence for an injector is known by historical data and experience.
The theoretical and practical information is supported with mature field examples to investigate the factors affecting the performance of vertical wells in tight and intermediate-permeability reservoirs along with the outline of the major challenges and how to solve them. This study also illustrates the challenges of application of CRM on a tight reservoir in the order of 0.1md and comparison of the application of the method on a more intermediate-perm reservoir. Field data used in this study is from publicly available, open access source, Division of Oil, Gas & Geothermal Resources (DOGGR) website - http://www.conservation.ca.gov/dog
California is known for being at the forefront of renewable technology adoption and greenhouse gas emissions curtailment. Even in an industry seen by many residents as archaic, oil producers are increasingly seeking out alternative sources of energy to use in operations. In 2011, Berry Petroleum and solar energy provider GlassPoint started up a 300-kW thermal project at McKittrick oilfield in Kern County that ultimately produced 1 million Btus/hr of solar heat over its 5-year lifespan while reducing the field's gas consumption. That same year, Chevron Technology Ventures and BrightSource Energy launched a 29-MW thermal solar-to-steam facility as part of a 3-year pilot project at Coalinga oilfield in Fresno County. Aera is teaming up with GlassPoint to build an 850-MW solar thermal facility to produce 12 million bbl/year of steam for reservoir injection and a 26.5-MW photovoltaic facility to generate electricity for operations.
Ghahfarokhi, Payam Kavousi (West Virginia University) | Carr, Timothy (West Virginia University) | Song, Liaosha (West Virginia University) | Shukla, Priyavrat (Schlumberger) | Pankaj, Piyush (Schlumberger)
Recently, oil and gas companies started to invest in fiber optic technology to remotely monitor subsurface response to stimulation. Distributed Acoustic Sensing (DAS) and Distributed Temperature Sensing (DTS) record vibration and temperature around the fiber, respectively. In this research, we introduce new seismic attributes calculated from the DAS data that could suggest cross-stage fluid communication during hydraulic fracturing. The DAS data covers the entire 28 stimulated stages of the lateral MIP-3H well close to Morgantown, WV. We calculated the energy attribute for the DAS data of the studied stages. Subsequently, a Hilbert transform is applied to the DAS data to evaluate the instantaneous frequency of each trace in the DAS. In addition, we applied a fast Fourier transform to each trace for all the SEGY files to calculate the dominant frequency with a 30 second temporal window. The dominant frequency is compared to the DTS data and energy attribute for the stages in the horizontal MIP-3H well. The DTS analysis shows that stimulation of the stages 10 causes a temperature rise in the previous stage 9; in contrast, stage 18 stimulation does not affect stage 17 temperature. We suggest that the common low frequency zone identified in instantaneous frequency and dominant frequency attributes between stages 10 and 9 is related to presence of fluid and gas that transferred cross-stage during hydraulic fracturing. The fluid and results in the frequency damping of the vibrations around the fiber. We show that the frequency attribute reveals increases detail about the stimulation than conventional signal energy attribute of the DAS data.
A rendering of Aera’s planned 850-MW solar EOR facility at Belridge field near Bakersfield, Calif. Startup is expected as early as 2020. California is known for being at the forefront of renewable technology adoption and greenhouse gas emissions curtailment. Even in an industry seen by many residents as archaic, oil producers are increasingly seeking out alternative sources of energy to use in operations. The high number of aging heavy oilfields, high quantity of sunshine, and state’s environmental sensibilities make for an ideal proving ground for a technology that brings two divergent industries together: solar thermal enhanced oil recovery (EOR).
A rendering of Aera’s planned 850-MW solar EOR facility at Belridge field near Bakersfield, California. Startup is expected as early as 2020. California is known for being at the forefront of renewable technology adoption and greenhouse gas emissions curtailment. Even in an industry seen by many residents as archaic, oil producers are increasingly seeking out alternative sources of energy to use in operations. In 2011, Berry Petroleum and solar energy provider GlassPoint started up a 300-kW thermal project at McKittrick oilfield in Kern County that ultimately produced 1 million Btus/hr of solar heat over its 5-year lifespan while reducing the field’s gas consumption.