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Abstract The filtrate contamination cleanup time on a complex carbonate well using a traditional wireline formation tester (WFT) tool can vary from a couple of hours to over half a day. The method proposed aims at reducing operational time to collect a low-contamination formation fluid sample by determining regions with a smaller depth of invasion using a forward model simulation that considers static and dynamic formation properties to predict the radial profile of invasion. The mud filtrate invasion process was modeled considering the static and dynamic properties of the near-wellbore region in an industry reference reservoir simulator, and it integrates three mechanisms for fluid flow: Darcy’s law, material balance, and capillary pressure. The physical robustness of the reservoir simulator was united to a data-driven model to reduce the computational cost. This proxy model is based on a trained neural network with a broad range of scenarios to predict the numerical simulation results with high accuracy. The invasion estimation from the model is then used to predict the filtrate cleanup time using an industry consolidated numerical modeling. One of the variables influencing most of the cleanup time is the depth of mud filtrate invasion. Thus, reducing this time is a determinant for the WFT operational efficiency. The model for mud invasion has been successfully tested on a complex carbonate well, and the results for the depth of mud invasion were comparable to the results obtained with a commercial data-driven inversion using multiple resistivity channels. The estimated cleanup time using the results of depth of invasion predicted by the forward model has been compared and matched with real carbonate sampling stations, and there was a high correlation indicating that zones with lower depth of invasion required less cleanup time. Besides, using the history-matched cases, different WFT technologies such as single and radial probes, focused, unfocused, and dual-packer WFT inlets were evaluated, showing a high potential for reduction of operational time when properly planned and selected for the specific type of reservoir. The proposed methodology is a viable method for understanding the clean-up behavior in different reservoir scenarios using different WFT technologies. The innovation of this method relies on the data calibration using basic and advanced petrophysical properties through a data-driven model based on a trained neural network to reduce the uncertainty in the predicted invasion radial profile and the WFT cleanup time. The reliability on the theoretical results was increased using real data calibration, and this calibrated theoretical model has been used to guide the sampling depth selection, saving operational time.
Abstract Data Science is the current gold rush. While many industries have benefitted from applications of data science, including machine learning and Artificial Intelligence (AI), the applications in upstream oil and gas are still somewhat limited. Some examples of applications of AI include seismic interpretations, facility optimization, and data driven modeling – forecasting. While still naïve, we will explore cases where data science can be used in the day to day field optimization and development. The Midway Sunset (MWSS) field in San Joaquin Valley, California has over 100 years of history. The field was discovered in 1901 and had limited development through the 1960s. Since the start of thermal stimulation in 1964, the field has seen phased thermal flooding and cyclic stimulation. Recently there has been an increase in heat mining vertical and horizontal wells to tap the remaining hot oil. As with any brownfield, the sweet spots are long gone. Effort is now to optimize the field development and tap by-passed oil, thereby increasing recovery. The current operational focus includes field wide holistic review of remaining resource potential. Resources in the MWSS reservoirs are produced by cyclic steam method. Cyclic thermal stimulation has been effective as an overall depletion process and for stimulating the near wellbore region to increase production. It is imperative to properly identify target wells and sands for cyclic stimulation. Cyclic steaming in depleted zones or cold reservoirs is often uneconomical. The benefit comes when we can identify and stimulate only the warm oil. Identification of warm oil and short listing the wells for cyclic stimulation is a labor-intensive process. The volume of data can get so large that it may not be feasible for a professional to effectively do the analysis. In this paper, we present a case study of data analytics for high grading wells for cyclic stimulation. This method utilizes the machine power to integrate reservoir, and production data to identify and rank wells for cyclic stimulation and potentially increase success rate by minimizing suboptimal cyclic candidates.
Summary Numerical simulation of coupled multiphase multicomponent flow and transport in porous media is a crucial tool for understanding and forecasting of complex industrial applications related to the subsurface. The discretized governing equations are highly nonlinear and usually need to be solved with Newton's method, which corresponds with high computational cost and complexity. With the presence of capillary and gravity forces, the nonlinearity of the problem is amplified even further, which usually leads to a higher numerical cost. A recently proposed operator-based linearization (OBL) approach effectively improves the performance of complex physical modeling by transforming the discretized nonlinear conservation equations into a quasilinear form according to state-dependent operators. These operators are approximated by means of a discrete representation on a uniform mesh in physical parameter space. Continuous representation is achieved through the multilinear interpolation. This approach provides a unique framework for the multifidelity representation of physics in general-purpose simulation. The applicability of the OBL approach was demonstrated for various energy subsurface applications with multiphase flow of mass and heat in the presence of buoyancy and diffusive forces. In this work, the OBL approach is extended for multiphase multicomponent systems with capillarity. Through the comparisons with a legacy commercial simulator using a set of benchmark tests, we demonstrate that the extended OBL scheme significantly improves the computational efficiency with the controlled accuracy of approximation and converges to the results of the conventional continuous approach with an increased resolution of parametrization. Introduction Numerical simulation, a tool developed by combining physics, mathematics, and computer programming, is an efficient way to understand the complex fluid flow in subsurface reservoirs with applications to the evaluation of hydrocarbon recovery, performance analysis, and various optimization problems (Todd et al. 1972; Spillette et al. 1973; Thomas and Thurnau 1983). It involves solving the partialdifferential equations governing coupled multiphase flow and transport in porous media with highly nonlinear physics (Aziz and Settari 1979; Coats et al. 1995).
This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper OTC 30626, “Brazil Presalt, Santos Basin: Feasibility Study for the Application of Borehole Gravity To Improve Reservoir Monitoring,” by Zhijun Du, Adrian Topham, SPE, and Jeremy C. Lofts, SPE, Silicon Microgravity, et al., prepared for the 2020 Offshore Technology Conference, originally scheduled to be held in Houston, 4-7 May. The paper has not been peer reviewed. Copyright 2020 Offshore Technology Conference. Reproduced by permission. The complete paper uses a feasibility study to present the potential application of a three-axis gravimeter borehole measurement in the Libra presalt reservoir in the Santos Basin offshore Brazil. The authors’ findings suggest that an annual survey with a limited well stock could be effective in monitoring this type of reservoir and that a wireline-deployed three-axis gravity tool is likely to provide significant additional surveillance to constrain a reservoir production strategy through better appreciation of the direction of water movement. Introduction The giant Brazilian presalt reservoirs are in ultradeep water (greater than 2000 m) and buried at a depth surpassing 5000 m. In order to conduct reservoir monitoring and achieve successful reservoir management, borehole-based geophysical technologies are preferred because the measurements can be made closer to the reservoir mass. The development of a borehole gravimeter suit-able for use in deep reservoirs, however, poses significant technical challenges, and breakthroughs have been limited by the sensor form factor (size) and measurement stabilization. By use of microelectromechanical-system (MEMS) vibrating-beam technology, the authors introduce a borehole gravimeter that enables the recording of gravitational acceleration at very high sensitivity. The new resonant MEMS gravitational sensor is designed to sense mass in the subsurface such that time-lapse wireline-based surveys can be conducted to build a picture of fluid movements at relatively large distances from a wellbore, thereby enabling time-lapse or 4D gravity monitoring. The innovation of the three-axis gravimeter also allows the acquisition of directional information about the spatial movement of fluid, even when acquired from only a single borehole. The principles of measuring gravity in the borehole environment are provided in the complete paper. Libra Field. The field is one of the largest presalt oil discoveries in the Santos Basin. It was discovered in May 2010 with recoverable resources of approximately 9 billion bbl of oil. The first appraisal well was completed and tested in February 2015. At the time of writing, nine appraisal wells have been drilled. A high-density 3D seismic program was acquired over the Santos and Campos basins, and advanced seismic processing technology has also been applied. Reservoir Simulation. The geophysics for reservoir characterization and simulation of these carbonate reservoirs is still in its early stages, and little published knowledge about their properties exists. Nonetheless, since their discovery, 2D and 3D seismic technologies have been applied intensively for imaging the region structures and delineating the reservoirs.
Han, Xiaodong (China University of Petroleum, Beijing, and China National Offshore Oil Corporation Ltd.) | Zhong, Liguo (China University of Petroleum, Beijing) | Wang, Xiang (Changzhou University) | Liu, Yigang (China National Offshore Oil Corporation Ltd.) | Wang, Hongyu (China National Offshore Oil Corporation Ltd.)
Summary The determination of optimal well locations and well controls in the horizontal-well steamflooding of heavy-oil reservoirs is a meaningful but also challenging task for the complex well types and complicated mechanisms. In this paper, a framework that combines optimization algorithms and the reservoir simulator together is proposed to solve this problem. Two typical algorithms, particle-swarm optimization (PSO) and mesh adaptive direct search (MADS), are both used to study their performance on well-placement optimization, well-control optimization, and the joint optimization of these two aspects. For the joint-optimization problem, both the simultaneous approach and sequential approach are considered. A net-present-value (NPV) formula for evaluation of the steamflooding project is proposed, and optimization runs are conducted for an offshore heavy-oil reservoir by maximizing the NPV of the horizontal steamflooding pilot. The results show that both the PSO and MADS were effective for well-placement/control optimization of the horizontal steamflooding wells. The NPVs were greatly improved throughout the optimization process. The control frequency has great influence on the optimal NPV. Intermittent steamflooding might be a better choice than continuous steamflooding. The steam-injection rate and oil-production rates need to be controlled and decreased at the latter stage for mitigating steam channeling and an ineffective steam cycle between injection and production wells. For the joint-optimization problem, the simultaneous procedure finds the best solution for a case with smaller variable numbers and the sequential procedure performs better for a case with larger variable numbers. The PSO algorithm performs better than the MADS algorithm for more complex problems with larger variable numbers in both the simultaneous and sequential procedures. The sequential procedure is worth considering in practice for problems with large scale and a limited computational budget.
Summary Hydrocarbon fields that are located offshore Abu Dhabi, United Arab Emirates (UAE), are known to be associated with undulating thick sedimentary sequences. These undulations are mostly influenced by variations in the depth of Infracambrian Hormuz salts that generate negative gravity anomalies. Nonetheless, a few known oil fields are uncorrelated with the airborne gravity observations. This is attributed to the interference from large positive gravity anomalies from basement highs. To filter out the effect of basement, we calculate the pseudogravity effect of the airborne magnetic anomalies and subtract it from the gravity anomalies. The resultant gravity anomalies mainly represent the effect of the salt domes. The results uncover deep salt structures and introduce potential traps for hydrocarbons that have proved difficult to map accurately with current seismic techniques. A nonlinear 3D inversion modeling of corrected magnetic and decreased gravity data is also used to determine the depth to basement and the Infracambrian Hormuz salts over two regions. Our findings demonstrate that the depth to basement in these regions changes from 7100 to 9700 m, and the depth to Infracambrian Hormuz salt changes from 5800 to 9400 m, with a variable thickness with a maximum of 2700 m.
Silva Neto, Gilson Moura (Petrobras, University of Campinas, and NORCE Norwegian Research Centre) | Soares, Ricardo Vasconcellos (NORCE Norwegian Research Centre, University of Bergen) | Evensen, Geir (NORCE Norwegian Research Centre and Nansen Environmental and Remote Sensing Center) | Davolio, Alessandra (University of Campinas) | Schiozer, Denis José (University of Campinas)
Summary Time-lapse-seismic-data assimilation has been drawing the reservoir-engineering community's attention over the past few years. One of the advantages of including this kind of data to improve the reservoir-flow models is that it provides complementary information compared with the wells' production data. Ensemble-based methods are some of the standard tools used to calibrate reservoir models using time-lapse seismic data. One of the drawbacks of assimilating time-lapse seismic data involves the large data sets, mainly for large reservoir models. This situation leads to high-dimensional problems that demand significant computational resources to process and store the matrices when using conventional and straightforward methods. Another known issue associated with the ensemble-based methods is the limited ensemble sizes, which cause spurious correlations between the data and the parameters and limit the degrees of freedom. In this work, we propose a data-assimilation scheme using an efficient implementation of the subspace ensemble randomized maximum likelihood (SEnRML) method with local analysis. This method reduces the computational requirements for assimilating large data sets because the number of operations scales linearly with the number of observed data points. Furthermore, by implementing it with local analysis, we reduce the memory requirements at each update step and mitigate the effects of the limited ensemble sizes. We test two local analysis approaches: one distance-based approach and one correlation-based approach. We apply these implementations to two synthetic time-lapse-seismic-data-assimilation cases, one 2D example, and one field-scale application that mimics some of the real-field challenges. We compare the results with reference solutions and with the known ensemble smoother with multiple data assimilation (ES-MDA) using Kalman gain distance-based localization. The results show that our method can efficiently assimilate time-lapse seismic data, leading to updated models that are comparable with other straightforward methods. The correlation-based local analysis approach provided results similar to the distance-based approach, with the advantage that the former can be applied to data and parameters that do not have specific spatial positions.
Each edition of the Olympic Games brings together remarkable athletes, volunteers, and spectators of all nationalities in a long-anticipated competition. While Brazil just finished hosting its first summer Olympics in the coastal city of Rio de Janeiro, in the world of oil and gas megaprojects another type of competition is in play--that of market share. More akin to a marathon race than a sprint, Olympic-sized oil and gas megaprojects take years to come to fruition and require billions of dollars in development costs. Not every planned megaproject will make it to the finish line. What does it take for these ultraambitious projects to succeed?
Pillars of the Industry features select contributions from experienced authors who have distinguished themselves by prolific careers and have made significant contributions to their fields of specialization. It is intended that readers find a source of inspiration that could help them shape their own contributions to the industry. In this issue, we have invited Michael Economides of the U. of Houston and Brian Glass and Carol Stoker of NASA's Ames Research Center to contribute to the discussion about peak oil and hot technologies. Economides explains why he is prudently optimistic about the world energy situation. He asserts that even though peak oil is a distinctive attribute of any depletable resource, it might never come to fruition in the case of oil.
Godhavn, John-Morten (Equinor) | Olorunju, Banzi (Equinor) | Gorski, Dmitri (Heavelock Solutions) | Kvernland, Martin (Heavelock Solutions) | Sant`Ana, Mateus (Heavelock Solutions) | Aamo, Ole Morten (Norwegian University of Science and Technology (NTNU)) | Sangesland, Sigbjørn (Norwegian University of Science and Technology (NTNU))
Summary In this paper, we describe measured and simulated downhole pressure variations (“surge and swab”) during drillpipe connections when drilling an ultradeepwater well offshore Brazil on Bacalhau (former Carcará) Field. Floating rig motion caused by waves and swell (“rig heave”) induces surge and swab when the drillstring is suspended in slips to make up or break a drillpipe connection and topside heave compensation is temporarily deactivated. This is a known issue in regions with harsh weather, such as the North Sea, where pressure oscillations of up to 20 bar have been reported during connections. Recorded downhole drilling data from Bacalhau Field reveals significant pressure oscillations downhole (in the same order of magnitude as in the North Sea) each time the drillstring was suspended in slips to make a connection in the subsalt 8½-in. section of the well. Mud losses were experienced around the same well depth, and they might have been caused by surge and swab. Measured surge and swab pressure variations have been reproduced in an advanced proprietary surge and swab simulator that considers rig heave, drillpipe elasticity, well friction, non-Newtonian drilling mud, well trajectory, and geometry. Moreover, findings in this paper suggest that surge and swab was in fact significantly higher than recorded by the measurement while drilling (MWD) tool. The true magnitude of surge and swab is not captured in the recorded MWD data due to low sampling frequency of the downhole pressure recording (one measurement every 6 seconds, a standard downhole pressure sampling rate used on many operations today). This work shows that surge and swab during drillpipe connections on floaters may challenge the available pressure window for some wells, even in regions with calm weather such as Brazil. Managed pressure drilling (MPD) is a technique that improves control of the downhole pressure. It is, however, not possible to compensate fast downhole pressure transients, such as heave-induced surge and swab, using MPD choke topside. This is due to the long distance between the choke and the bit, which translates into a time delay in the same order of magnitude as typical wave and heave periods. A downhole choke combined with continuous circulation is one of the potential solutions. Surge and swab during drillpipe connections can result in a loss or an influx and should be considered in the well planning phase when mud weight, section lengths, etc. are selected.