All cancellations must be received no later than 14 days prior to the course start date. Cancellations made after the 14 day window will not be refunded. Refunds will not be given due to no show situations. Training sessions attached to SPE conferences and workshops follow the cancellation policies stated on the event information page. Please check that page for specific cancellation information. SPE reserves the right to cancel or re-schedule courses at will. Notification of changes will be made as quickly as possible; please keep this in mind when arranging travel, as SPE is not responsible for any fees charged for cancelling or changing travel arrangements. We reserve the right to substitute course instructors as necessary. Full regional cancellation policies can be found at the Cancellation Policy page within the SPE Training Course Catalog.
Li, Nianyin (State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University) | Yang, Ming (State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University) | Zhang, Qian (State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University) | Zhou, Hongyu (Natural Gas Research Institute of PetroChina Southwest Oil and Gas Field Company) | Zhai, Changjin (Zhanjiang branch of CNOOC Co. Ltd.) | Feng, Lei (CNOOC EnerTech-Drilling & Production Co.)
Matrix acidizing is an essential strategy to maintain or increase productivity or injectivity of hydro-carbon wells. However, for loose sandstone reservoirs, the rock skeleton structure is easily de-stroyed by acidizing with conventional acid systems, which results in sand production. Also, the precipitation of metal fluorides, fluorosilicates, and so forth that may occur during acidizing will cause secondary damage to reservoirs. Therefore, we propose a new multiple chelating acid system (NMCAS) with low damage and weak dissolution. The system consists of multiple weak acids, organic phosphonic chelators, anionic polycarboxylic chelating dispersants, fluorides, and other auxiliary additives. Its performance was measured through laboratory tests. First, the dissolution retardation effect and dissolution capacity of NMCAS were analyzed by long-term dissolution tests. Then, the changes of particle size and mineral composition of the rock powder before and after dissolution of NMCAS and a regular mud acid system were comparatively analyzed by a sieving analysis method and x-ray diffraction measurement. Third, the chelating abilities of the system on metal ions were analyzed by a titration method. Moreover, the improvement of seepage capacity was analyzed by a core acidification flowing experiment and scanning electron microscopy. Finally, the dissolution mechanism of the system was further analyzed by energy dispersive spectroscopy. Research results indicate that NMCAS has a good retardation effect and a moderate dissolution ability. After dissolution of rock powder with the proposed acid system, the changes in particle size were less than those of the conventional mud acid system. Also, it dissolved merely a small portion of the clay minerals, but increased the dissolution of quartz, feldspar, and other matrices. NMCAS can prevent secondary precipitation of metal ions during the acidizing process because of its strong chelating ability for calcium ions, magnesium ions, and iron ions. The permeability of sample cores was moderately increased, and they formed obvious dissolution channels; however, the rock skele-ton structure was not destroyed after acidizing with NMCAS. This is because the system reduced the dissolution of clay minerals with larger specific surfaces because of the adsorption effect (a relatively lower reduction in the content of the Al element) while enhancing that of such matrices as quartz and feldspar (relatively larger changes in the content of the Si element). NMCAS can dis-solve the cement appropriately while enhancing the dissolution of the matrices, which protects the rock skeleton structure of loose sandstone reservoirs. The proposed acid solution would be of value for removing formation plugging and increasing the production of loose sandstone reservoirs.
Tewari, Saurabh (Rajiv Gandhi Institute of Petroleum Technology, India) | Dwivedi, U. D. (Rajiv Gandhi Institute of Petroleum Technology, India) | Shiblee, Mohammed (King Khalid University, Saudi Arabia)
Production of oil & gas depends upon the recoverable amount of hydrocarbon existing beneath the underlying reservoir. Reservoir recovery factor provides of the production potential of ‘proven reservoirs’ which helps the planning of field development and production. Estimation of reservoir recovery factor, with a good degree of accuracy, is still a challenging task for engineers due to the high level of uncertainty, large inexactness, noise, and high dimensionality associated with reservoir measurements. In this paper, we propose a big data-driven ‘ensemble estimator’ (E2) module, comprising of wavelet associated ensemble models for the estimation of reservoir recovery factor. All the ensemble models in E2 were trained on big reservoir data and tested with unknown reservoir data samples obtained from U.S.A. oil & gas fields. Bagging and Random forest ensembles have been utilized to correlate several reservoir properties with reservoir recovery factor. Further, E2 utilizes Relief algorithm to understand the significance of reservoir properties effecting the recovery factor of a reservoir. The proposed E2 module has provided impressive estimation results for the determination of reservoir recovery factor with minimum prediction error. Random forest has given the highest coefficient of correlation (R2=0.9592) and minimum estimation errors viz. mean absolute error (MAE=0.0234) and root mean square error (RMSE=0.0687). The performance of the proposed E2 module was also compared with conventional estimators viz. Radial basis function, Multilayer perceptron, Regression tree and Support vector regression. The experimental results have demonstrated the supremacy of E2 over conventional learners for the estimation of reservoir recovery factor.
Alkinani, Husam H. (Missouri University of Science and Technology) | Al-Hameedi, Abo Taleb T. (Missouri University of Science and Technology) | Dunn-Norman, Shari (Missouri University of Science and Technology) | Flori, Ralph E. (Missouri University of Science and Technology) | Alsaba, Mortadha T. (Australian College of Kuwait) | Amer, Ahmed S. (Newpark Technology Center/ Newpark Drilling Fluids)
Oil/gas exploration, drilling, production, and reservoir management are challenging these days since most oil and gas conventional sources are already discovered and have been producing for many years. That is why petroleum engineers are trying to use advanced tools such as artificial neural networks (ANNs) to help to make the decision to reduce nonproductive time and cost. A good number of papers about the applications of ANNs in the petroleum literature were reviewed and summarized in tables. The applications were classified into four groups; applications of ANNs in explorations, drilling, production, and reservoir engineering. A good number of applications in the literature of petroleum engineering were tabulated. Also, a formalized methodology to apply the ANNs for any petroleum application was presented and accomplished by a flowchart that can serve as a practical reference to apply the ANNs for any petroleum application. The method was broken down into steps that can be followed easily. The availability of huge data sets in the petroleum industry gives the opportunity to use these data to make better decisions and predict future outcomes. This paper will provide a review of applications of ANNs in petroleum engineering as well as a clear methodology on how to apply the ANNs for any petroleum application.
Guo, Zhenyu (University of Tulsa) | Chen, Chaohui (Shell Exploration and Production Company Incorporated) | Gao, Guohua (Shell Global Solutions US Incorporated) | Cao, Richard (Shell Exploration and Production Company Incorporated) | Li, Ruijian (Shell Exploration and Production Company Incorporated) | Liu, Hope (Shell Exploration and Production Company Incorporated)
Reservoir model parameters generally have very large uncertainty ranges, and need to be calibrated by history matching (HM) available production data. Properly assessing the uncertainty of production forecasts (e.g., with an ensemble of calibrated models that are conditioned to production data) has a direct impact on business decision making. It requires performing numerous reservoir simulations on a distributed computing environment. Because of the current low-oil-price environment, it is demanding to reduce the computational cost of generating multiple realizations of history-matched models without compromising forecasting quality. To solve this challenge, a novel and more efficient optimization method (referred to as SVR-DGN) is proposed in this paper, by replacing the less accurate linear proxy of the distributed Gauss-Newton (DGN) optimization method (referred to as L-DGN) with a more accurate response-surface model of support vector regression (SVR).
Resembling L-DGN, the proposed SVR-DGN optimization method can be applied to find multiple local minima of the objective function in parallel. In each iteration, SVR-DGN proposes an ensemble of search points or reservoir-simulation models, and the flow responses of these reservoir models are simulated on high-performance-computing (HPC) clusters concurrently. All successfully simulated cases are recorded in a training data set. Then, an SVR proxy is constructed for each simulated response using all training data points available in the training data set. Finally, the sensitivity matrix at any point can be calculated analytically by differentiating the SVR models. SVR-DGN computes more-accurate sensitivity matrices, proposes better search points, and converges faster than L-DGN.
The quality of the SVR proxy is validated with a toy problem. The proposed method is applied to a real field HM example of a Permian liquid-rich shale reservoir. The uncertain parameters include reservoir static properties, hydraulic-fracture properties, and parameters defining relative permeability curves. The performance of the proposed SVR-DGN optimization method is compared with the L-DGN optimizer and the hybrid Gauss-Newton with a direct-pattern-search (GN-DPS) optimizer, using the same real field example. Our numerical tests indicate that the SVR-DGN optimizer can find better solutions with smaller values of the objective function and with a less computational cost (approximately one-third of L-DGN and 1/30 of GN-DPS). Finally, the proposed method is applied to generate multiple conditional realizations for the uncertainty quantification of production forecasts.
Despite decades of numerical, analytical and experimental researches, sand production remains a significant operational challenge in petroleum industry. Amongst all techniques, analytical solutions have gained more popularity in industry applications because the numerical analysis is time consuming; computationally demanding and solutions are unstable in many instances. Analytical solutions on the other hand are yet to evolve to represent the rock behaviour more accurately.
We therefore developed a new set of closed-form solutions for poro-elastoplasticity with strain softening behaviour to predict stress-strain distributions around the borehole. A set of hollow cylinder experiments was then conducted under different compression scenarios and 3D X-Ray Computed Tomography was performed to analyse the internal structural damage. The results of the proposed analytical solutions were compared with the experimental results and good agreement between the model prediction and experimental data was observed. The model performance was then tested by analysing the onset of sand production in a well drilled in Bohai Bay in Northeast of China. Acoustic and density log along with core data were used to provide the input parameters for the proposed analytical model in order to predict the potential sanding in this well. The proposed solution predicted the development of a significant plastic zone thus confirming sand production observed by today sanding issue in this well.
In the Freeman Field, located about 120km offshore southwestern Niger Delta at about 1300m water depth, 3D seismic attribute-based analogs, and structural and stratigraphic based geometric models are combined to help enhance and constrain interpretation. The objective of this research was to aid in the prospecting of Miocene to Pliocene Agbada Formation reservoirs in the deep offshore Niger Delta Basin. Multidisciplinary approaches – analysis of root-mean-square amplitude attribute, iterative integrated seismic interpretation and structural modeling, were employed in this study. Results reveal a massive northwest-southeast trending shale-cored detachment fold anticline containing numerous associated normal faults. This structure is interpreted to have been deformed by differential loading of the undercompacted, overpressured, and ductile Akata shale during syndepositional gravitational collapse of the Niger Delta slope. Crestal extension in the anticline resulted in a complex array of synthetic and antithetic normal faults, which include crossing-conjugate pairs. These conjugate structures could significantly affect permeability and reservoir performance. Crossing-conjugate faults have not previously been recognized in the Niger Delta, and similar structures may be present in other hydrocarbon-trapping structures in the basin. Also, the Miocene to Pliocene Agbada Formation reservoirs occur as part of a channelized fan system, mostly deposited as turbidites in an unconfined distributary environment, except one reservoir sand that occurs as channel sand within a submarine canyon that came across and eroded a previously deposited distributary fan complex, suggesting likely presence of prospective areas for hydrocarbon exploration southwest of the Freeman Field.
Presentation Date: Thursday, October 18, 2018
Start Time: 8:30:00 AM
Location: 210A (Anaheim Convention Center)
Presentation Type: Oral
Society of Petroleum Engineers - Copyright transferred to SPE by Larry Moore on behalf of Preston L. Moore.
Dubey, Pranav (Indian School of Mines) | Okpere, Adrian (Shell Petroleum Development Company of Nigeria) | Sanni, Gideon (Shell Petroleum Development Company of Nigeria) | Onyeukwu, Ifeanyi (Flowgrid)
An optimized completion design that addresses gaps in the existing single well Producer-Injector (P-I) concept is presented in this paper. Field development scenarios based on the optimized P-I concept and conventional waterflood were implemented in full-field 3D simulation models.
Detailed review of the existing single P-I well concept revealed gaps in the completion design with regards to feasibility of data acquisition, ease of well intervention and well safety/control. The existing design utilizes a Single-String-Single (SSS) design with through-tubing water injection and oil production through annulus, whilst the optimized design is a Two-String-Dual (TSD) incorporating the flexibility of independent injection/production, zonal isolation for interventions & data acquisition and additional safety completion jewelries.
A fit-for-purpose reservoir candidate was selected by assessing it’s suitability to waterflooding. The reservoir belongs to the paralic sequence of the Agbada Formation of the Niger Delta basin - a sequence of interbedded sandstones and shales. The reservoir is an elongated anticline bounded by W-E oriented faults and exhibiting channelized shoreface sediments. Porosity and permeability ranges are 17-31% and 200mD-2200mD respectively. Shale baffles strongly reduces the influence of the aquifer hence the simulation model is an oil reservoir with weak aquifer completed by the P-I well producing oil and injecting into the aquifer in tandem. Performance of the single P-I well strategy was benchmarked against conventional waterflood patterns to effectively capture the recovery efficiency and production forecast for each scenario.
Results from the five-parameter experimental design based on the P-I strategy, indicate Ultimate Oil Recovery is most impacted by horizontal permeability; injection rate, flow barrier transmissibility and vertical permeability with the least influence. Dynamic 3D water saturation maps show the waterflood front propagating principally in the horizontal direction from the injector, providing important reservoir boundary pressure support and minimizing the chance for injected water short-circuiting at the sandface.
Ultimate Oil Recovery of 5spot/line drive patterns and the P-I strategy were similar, 54% and 52% respectively. Well completion costs and forecasts were fed into simple economics spreadsheet to test which technique provides the most value. Open book economics results showed the P-I concept provides better value (NPV 23.0 and VIR 0.67) than 5 spot and line drive patterns (NPV -17 and VIR -0.14).
Oseme, Ugochukwu (Shell Petroleum Development Company) | Awe, Sunday (Shell Petroleum Development Company) | Amah, Obinna (Shell Petroleum Development Company) | Erinle, Adeyemi (Shell Petroleum Development Company) | Akinfolarin, Ayodele (Shell Petroleum Development Company) | Ibrahim, Timothy (Shell Petroleum Development Company) | Roes, Vincent (Shell Petroleum Development Company)
Application of Managed pressure drilling (MPD) technology with other techniques to maintain constant Bottom Hole pressure (BHP) has been found to enhance drilling operations in applications where the margin between the pore pressure and fracture gradient is narrow and the reservoir permeability is high. Classic examples of such applications are deep water drilling, high pressure and high temperature (HPHT) regime and depleted reservoir environments.
In the Niger Delta, HPHT reservoirs can be found in well depths up to 17000 ftss with a drilling window range of 0.4 to1.6ppg. Typical reservoir characteristics are formation permeability of 124 - 204mD and reservoir mobility of 112 – 1000mD/cp. Generally in this type of environment and essentially where there are high uncertainties in the reservoir pressures and formation characteristics, significant process safety incidents have been found to occur during pumps off events as a result of variations in BHP outside the allowable limits of pore pressure (lower limit) and fracture gradient (upper limit). The risks of exceeding the allowable limits are the possibility of taking significant influx volume if BHP falls below the pore pressure and loss of well bore integrity if the BHP exceeds the fracture pressure. Consequences of any of these events are high nonproductive time (NPT), well cost escalation and inability to achieve well objectives.
This paper illustrates how in the recent HPHT exploration campaign carried out in Niger Delta, managing BHP was identified as a critical success factor. Hydrocarbon reserves of the exploratory objectives were successfully and safely unlocked by using MPD to maintain BHP within the allowable limits. The paper also illustrates how MPD application was enhanced by the use of high resolution pressure while drilling (PWD) technology.