Emulsions are always a drain on the operating budget. It is almost impossible to eliminate emulsions during crude production; however, emulsion problems can be reduced and optimized by following good operating practices. The following points should be included in operating practices. Chemical-Demulsifier Development Based on Critical-Electric-Field Measurements. Husveg, T., Bilstad, T., Guinee, P.G.A. et al. 2009 A Cyclone based Low Shear Valve for Enhanced Oil-Water Separation.
Selecting the best tool for a specific type of reservoir condition is a crucial part of a fluid sampling job. Moreover, uncertainty in sample quality increases when the fluid phases are miscible. On a recent logging job, a formation tester was used to acquire water samples across a zone drilled with water-base mud (WBM). We examine the performance of several probe configurations (both existing and prototype) under equivalent reservoir conditions to quantify and optimize filtrate cleanup efficiency. The study is carried out using a compositional simulator for a water-saturated reservoir invaded with blue-dye tracer included in WBM filtrate.
History matching of field measurements allows the calibration of the model for further modification to account for a variety of reservoir conditions. Complex tracer dynamics of a blue-dye WBM invading a water-saturated formation and fluid pumpout are accurately and expediently modeled using a flexible numerical algorithm to account for different probe types and tool configurations. Under normal operating conditions, the chosen formation tester would have taken around one hour to clean the filtrate contamination to a target value of 5%. On the other hand, the best choice was the Focused Elliptical Probe, for which fluid cleanup would take less than 40 minutes. Additionally, a different tool configuration with a combination of multiple probe geometries spaced radially around the tool would provide faster cleanup times of only 32 minutes, thereby saving rig time.
We rank eight formation testing tools designs under equivalent reservoir conditions. The examples highlight the importance of probe geometry and configurations together with reliable and expedient numerical modeling during the pre-job phase to reduce cleanup time in anticipation of complex reservoir conditions. Furthermore, numerical simulations compare the fluid cleanup efficiency for various commercial formation-testing probes together with innovative probe designs that could potentially lead to a new tool or probe development. Perfecting both probe geometry and fluid pumping schedule is the most important output of our study.
Recent studies have indicated that Huff-n-Puff (HNP) gas injection has the potential to recover an additional 30-70% oil from multi-fractured horizontal wells in shale reservoirs. Nonetheless, this technique is very sensitive to production constraints and is impacted by uncertainty related to measurement quality (particularly frequency and resolution), and lack of constraining data. In this paper, a Bayesian workflow is provided to optimize the HNP process under uncertainty using a Duvernay shale well as an example.
Compositional simulations are conducted which incorporate a tuned PVT model and a set of measured cyclic injection/compaction pressure-sensitive permeability data. Markov chain Monte Carlo (McMC) is used to estimate the posterior distributions of the model uncertain variables by matching the primary production data. The McMC process is accelerated by employing an accurate proxy model (kriging) which is updated using a highly adaptive sampling algorithm. Gaussian Processes are then used to optimize the HNP control variables by maximizing the lower confidence interval (μ-σ) of cumulative oil production (after 10 years) across a fixed ensemble of uncertain variables sampled from posterior distributions.
The uncertain variable space includes several parameters representing reservoir and fracture properties. The posterior distributions for some parameters, such as primary fracture permeability and effective half-length, are narrower, while wider distributions are obtained for other parameters. The results indicate that the impact of uncertain variables on HNP performance is nonlinear. Some uncertain variables (such as molecular diffusion) that do not show strong sensitivity during the primary production strongly impact gas injection HNP performance. The results of optimization under uncertainty confirm that the lower confidence interval of cumulative oil production can be maximized by an injection time of around 1.5 months, a production time of around 2.5 months, and very short soaking times. In addition, a maximum injection rate and a flowing bottomhole pressure around the bubble point are required to ensure maximum incremental recovery. Analysis of the objective function surface highlights some other sets of production constraints with competitive results. Finally, the optimal set of production constraints, in combination with an ensemble of uncertain variables, results in a median HNP cumulative oil production that is 30% greater than that for primary production.
The application of a Bayesian framework for optimizing the HNP performance in a real shale reservoir is introduced for the first time. This work provides practical guidelines for the efficient application of advanced machine learning techniques for optimization under uncertainty, resulting in better decision making.
One of the main uncertainties when designing polymer floods is the polymer injectivity, an important parameter that can affect the economics of the process. Reservoir simulation can be used to forecast injectivity, but the process is not straightforward and can be affected by grid size and other factors. Analytical methods are also available for that purpose, but they are considered too simplistic to deal with realistic reservoir conditions. The aim of this paper is to show that this is not the case and that simple analytical tools can be accurate and of great help to predict or history match polymer injectivity.
The analytical method has been developed by Lake in his classical textbook on Enhanced Oil Recovery, but few applications are documented in the literature. This paper will review the method and corresponding equations before presenting several actual field cases of injectivity in polymer flood pilots or tests from several countries that have been matched analytically.
Although it has not been used very often, the method has been found to give very good results in most of the field cases tested in a variety of situations; these cases will be presented along with recommendations on how to apply the method and a discussion of the results. Sensitivities to the various parameters will also be presented. Once the equations are programmed in a spreadsheet, the matching process takes only a few minutes and it is easy to run various scenarios and sensitivities.
Polymer injectivity remains one of the less understood and less predictable aspects of polymer flood projects. This paper will encourage engineers who are planning such projects to use simple yet accurate analytical tools before embarking in more complex and time-consuming reservoir simulations.
The benchmark comes as operator Eni solidifies concession agreements and ramps up exploration and development in the North African country. Touted as the Mediterranean Sea’s largest-ever gas discovery, the “supergiant” Zohr field is expected to cover much of Egypt’s gas demand in the coming decades.
The Apollonia tight-gas chalk play is located in the Abu Gharadig Basin in the Western Desert of Egypt. This has long been ignored as a gas play in the overburden, while the Jurassic and Cretaceous oil fields deeper in the basin have been explored and developed. Large areas of the North Sea contain Cretaceous sediments, which form a massive hard layer of chalk that historically has presented a major drilling risk and expense to operators in the area.
The Apollonia tight-gas chalk play is located in the Abu Gharadig Basin in the Western Desert of Egypt. This has long been ignored as a gas play in the overburden, while the Jurassic and Cretaceous oil fields deeper in the basin have been explored and developed. Dubai Petroleum embarked on a new mission last year to drill and complete its first multistage, hydraulically fractured, and propped horizontal well from an offshore platform. This paper gives the recommended MSF horizontal-well spacing for several development scenarios in Saudi Arabian gas-reservoir environments. A tight gas carbonate reservoir with no oil rim in a supergiant onshore gas field in Abu Dhabi was targeted for stimulation during a field review to increase field production.
The benchmark comes as operator Eni solidifies concession agreements and ramps up exploration and development in the North African country. Touted as the Mediterranean Sea’s largest-ever gas discovery, the “supergiant” Zohr field is expected to cover much of Egypt’s gas demand in the coming decades. Untapped offshore gas reservoirs could easily meet all of the country's domestic needs, while the rest could supply regional neighbors.
SPE is educating the next generation of aspiring engineers, scientists and managers about the oil and gas industry. This is an opportunity for school students in grades 9–12, studying Mathematics, Physics, Chemistry, Geography or interested in Petroleum Engineering are invited to join SPE members from all over the globe to discover the world of Petroleum Engineering. School teachers are invited to bring a group of 10–15 students. Students will be treated to a range of hands-on activities and presentations from renowned engineers. The oil price outlook coupled with the response of each oil and gas company to make ends meet has led to severe exploration budget cuts.