Tupi Nodes pilot: A successful 4D seismic case for Brazilian presalt reservoirs

2021 ◽  
Vol 40 (12) ◽  
pp. 886-896
Author(s):  
Nathalia Martinho Cruz ◽  
José Marcelo Cruz ◽  
Leonardo Márcio Teixeira ◽  
Mônica Muzzette da Costa ◽  
Laryssa Beatriz de Oliveira ◽  
...  
Keyword(s):  
Oil Recovery ◽  
History Matching ◽  
Oil And Gas ◽  
Feasibility Studies ◽  
Oil And Gas Industry ◽  
Time Lapse ◽  
Seismic Inversion ◽  
Carbonate Reservoirs ◽  
Ocean Bottom ◽  
4D Seismic

The oil and gas industry has established 4D seismic as a key tool to maximize oil recovery and operational safety in siliciclastic and low- to medium-stiffness carbonate reservoirs. However, for the stiffer carbonate reservoirs of the Brazilian presalt, the value of 4D seismic is still under debate. Tupi Field has been the stage of a pioneering 4D seismic project to field test the time-lapse technique's ability in monitoring production and water-alternating-gas (WAG) injection in the Brazilian presalt. Ocean-bottom node (OBN) technology was applied for the first time in the ultra-deep waters of Santos Basin, leading to the Tupi Nodes pilot project. We started with feasibility studies to forecast the presalt carbonate time-lapse responses. The minerals that constitute these carbonate rocks have an incompressibility modulus that is generally twice as large as those of siliciclastic rocks. This translates into discrete 4D signals that require enhanced seismic acquisition and processing techniques to be correctly detected and mapped. Consequently, two OBN seismic acquisitions were carried out. Time-lapse processing included the application of top-of-the-line processing tools, such as interbed multiple attenuation. The resulting 4D amplitude images demonstrate good signal-to-noise ratio, supporting both static and dynamic interpretations that are compatible with injection and production histories. To unlock the potential of 4D quantitative interpretation and the future employment of 4D-assisted history-matching workflows, we conducted a 4D seismic inversion test. Acoustic impedance variations of about 1.5% are reliably distinguishable beyond the immediate vicinity of the wells. These 4D OBN seismic surveys and interpretations will assist in identifying oil-bypassed targets for infill wells and calibrating WAG cycles, increasing oil recovery. We anticipate that studies of the entire Brazilian presalt section will greatly benefit from the results and conclusions already reached for Tupi Field.

scholarly journals Synergizing Crosswell Seismic and Electromagnetic Techniques for Enhancing Reservoir Characterization

SPE Journal ◽  
2016 ◽  
Vol 21 (03) ◽  
pp. 909-927 ◽  
Author(s):  
Klemens Katterbauer ◽  
Ibrahim Hoteit ◽  
Shuyu Sun
Keyword(s):  
History Matching ◽  
Oil And Gas ◽  
Reservoir Characterization ◽  
Saline Water ◽  
Oil And Gas Industry ◽  
Time Lapse ◽  
Gas Industry ◽  
Matching Process ◽  
Weak Density ◽  
Reservoir History Matching

Summary Increasing complexity of hydrocarbon projects and the request for higher recovery rates have driven the oil-and-gas industry to look for a more-detailed understanding of the subsurface formation to optimize recovery of oil and profitability. Despite the significant successes of geophysical techniques in determining changes within the reservoir, the benefits from individually mapping the information are limited. Although seismic techniques have been the main approach for imaging the subsurface, the weak density contrast between water and oil has made electromagnetic (EM) technology an attractive complement to improve fluid distinction, especially for high-saline water. This crosswell technology assumes greater importance for obtaining higher-resolution images of the interwell regions to more accurately characterize the reservoir and track fluid-front developments. In this study, an ensemble-Kalman-based history-matching framework is proposed for directly incorporating crosswell time-lapse seismic and EM data into the history-matching process. The direct incorporation of the time-lapse seismic and EM data into the history-matching process exploits the complementarity of these data to enhance subsurface characterization, to incorporate interwell information, and to avoid biases that may be incurred from separate inversions of the geophysical data for attributes. An extensive analysis with 2D and realistic 3D reservoirs illustrates the robustness and enhanced forecastability of critical reservoir variables. The 2D reservoir provides a better understanding of the connection between fluid discrimination and enhanced history matches, and the 3D reservoir demonstrates its applicability to a realistic reservoir. History-matching enhancements (in terms of reduction in the history-matching error) when incorporating both seismic and EM data averaged approximately 50% for the 2D case, and approximately 30% for the 3D case, and permeability estimates were approximately 25% better compared with a standard history matching with only production data.

Characterization of Matrix Wettability and Mass Transfer From Matrix to Fractures in Carbonate Reservoirs

2012 ◽  
Author(s):  
Anuj Gupta
Keyword(s):  
Oil Recovery ◽  
History Matching ◽  
Oil And Gas ◽  
Fractured Reservoirs ◽  
Naturally Fractured Reservoirs ◽  
Carbonate Reservoirs ◽  
Shape Factors ◽  
Naturally Fractured ◽  
Fractured Carbonate ◽  
The Matrix

This paper presents results of an experimental investigation, supported by numerical analysis, to characterize oil recovery from fractured carbonate reservoirs. Imbibition recovery of oil is measured as a function of time for samples with varying wettability and shape factors. One of the objectives of this study is to verify the validity of exponential transfer function for matrix-fracture systems with varying wettability and flow-boundary conditions. Another objective is to establish the possibility of quantitatively determining the wettability of a sample based on history-matching of cumulative imbibition recovery and recovery rate data. The productivity of most carbonate oil and gas reservoirs is closely tied to the natural or stimulated fracture system present in the reservoir. Further, the recovery from naturally fractured reservoirs, in presence of aquifer drive or waterflooding is closely tied to the wettability of the matrix. The approach presented in this paper offers means to evaluate how recovery factor in a fractured system can be affected by wettability. A detailed understanding of rock-fluid interactions and wettability alterations at the fracturing face should help design improved strategies for exploiting naturally fractured carbonate reservoirs.

Guest Editorial: Artificial Intelligence in the E&P Industry: What Have We Learned So Far and Where to Next?

2021 ◽  
Vol 73 (01) ◽  
pp. 12-13
Author(s):  
Manas Pathak ◽  
Tonya Cosby ◽  
Robert K. Perrons
Keyword(s):  
Artificial Intelligence ◽  
Science Fiction ◽  
Oil Recovery ◽  
Oil And Gas ◽  
Autonomous Systems ◽  
Oil And Gas Industry ◽  
Human Judgment ◽  
Gas Industry ◽  
The Media ◽  
And Function

Artificial intelligence (AI) has captivated the imagination of science-fiction movie audiences for many years and has been used in the upstream oil and gas industry for more than a decade (Mohaghegh 2005, 2011). But few industries evolve more quickly than those from Silicon Valley, and it accordingly follows that the technology has grown and changed considerably since this discussion began. The oil and gas industry, therefore, is at a point where it would be prudent to take stock of what has been achieved with AI in the sector, to provide a sober assessment of what has delivered value and what has not among the myriad implementations made so far, and to figure out how best to leverage this technology in the future in light of these learnings. When one looks at the long arc of AI in the oil and gas industry, a few important truths emerge. First among these is the fact that not all AI is the same. There is a spectrum of technological sophistication. Hollywood and the media have always been fascinated by the idea of artificial superintelligence and general intelligence systems capable of mimicking the actions and behaviors of real people. Those kinds of systems would have the ability to learn, perceive, understand, and function in human-like ways (Joshi 2019). As alluring as these types of AI are, however, they bear little resemblance to what actually has been delivered to the upstream industry. Instead, we mostly have seen much less ambitious “narrow AI” applications that very capably handle a specific task, such as quickly digesting thousands of pages of historical reports (Kimbleton and Matson 2018), detecting potential failures in progressive cavity pumps (Jacobs 2018), predicting oil and gas exports (Windarto et al. 2017), offering improvements for reservoir models (Mohaghegh 2011), or estimating oil-recovery factors (Mahmoud et al. 2019). But let’s face it: As impressive and commendable as these applications have been, they fall far short of the ambitious vision of highly autonomous systems that are capable of thinking about things outside of the narrow range of tasks explicitly handed to them. What is more, many of these narrow AI applications have tended to be modified versions of fairly generic solutions that were originally designed for other industries and that were then usefully extended to the oil and gas industry with a modest amount of tailoring. In other words, relatively little AI has been occurring in a way that had the oil and gas sector in mind from the outset. The second important truth is that human judgment still matters. What some technology vendors have referred to as “augmented intelligence” (Kimbleton and Matson 2018), whereby AI supplements human judgment rather than sup-plants it, is not merely an alternative way of approaching AI; rather, it is coming into focus that this is probably the most sensible way forward for this technology.

scholarly journals DETERMINATION OF THE SUSTAINABILITY OF THE PROJECT PORTFOLIO OF THE OIL AND GAS SECTOR OF THE ECONOMY TO EXTERNAL FACTORS

2021 ◽  
pp. 32-40
Author(s):  
L.S. Leontieva ◽  
◽  
E.B. Makarova ◽  
Keyword(s):  
Oil Recovery ◽  
Portfolio Management ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
External Factors ◽  
Project Portfolio ◽  
Project Portfolio Management ◽  
Oil And Gas Companies ◽  
Oil And Gas Sector

The oil and gas sector of the economy in many states remains the main source of foreign exchange and tax revenues to the budget. Moreover, its share, for example, in Russia, accounts for about 12 % of all industrial production. However, this sector, as the practice of world oil prices shows, is experiencing not only a rise, but also a decline. Consequently, the problem of forming a balanced portfolio of oil and gas assets is an object of close attention on the part of national oil and gas companies. The issues of choosing the optimal combination of oil and gas assets in the portfolio are no less urgent, especially among the tasks that all oil and gas companies face, both in Russia and abroad. An investment portfolio or a portfolio of oil and gas assets, which includes new projects for the commissioning of fields, as well as measures to enhance oil recovery, and exploration are objects of real investment. The high volatility of the oil and gas industry is influenced by various factors, including: macroeconomic, innovation risks and a number of others. These circumstances stimulate the sector to increase the resilience of its project portfolios in order to respond flexibly to changes. In an increasingly challenging and uncertain environment, oil and gas companies around the world face constant pressures as difficult strategic decisions and building long-term plans lead to a sustainable portfolio. In order to achieve their goals and maximize profitability, companies should apply certain algorithms in their practice. The article substantiates the role and importance of project portfolio management in achieving the goals of the state and companies in the oil and gas sector. The main goal of the article is to build an algorithm that is aimed both at determining the stability of the portfolio and the ability to flexibly respond to changes in the environment. The scientific novelty of the research lies in the determination of an algorithm for assessing the sustainability of a portfolio of projects of oil and gas companies. Application of this algorithm will allow oil and gas companies to take into account the influence of external factors. The research methodology is based on such methods as analysis of internal regulations and reporting of companies for project portfolio management, risk analysis, project ranking; grouping and classification method.

Finite Element Analysis of Casing Material Behavior in Steam Injection Well Operations

2015 ◽  
Vol 799-800 ◽  
pp. 196-200
Author(s):  
Abhilash M. Bharadwaj ◽  
Sonny Irawan ◽  
Saravanan Karuppanan ◽  
Mohamad Zaki bin Abdullah ◽  
Ismail bin Mohd Saaid
Keyword(s):  
Finite Element ◽  
Oil Recovery ◽  
Thermal Stresses ◽  
Oil And Gas ◽  
Extreme Temperature ◽  
Injection Pressure ◽  
Oil And Gas Industry ◽  
Steam Injection ◽  
Material Behavior ◽  
Element Analysis

Casing design is one of the most important parts of the well planning in the oil and gas industry. Various factors affecting the casing material needs to be considered by the drilling engineers. Wells partaking in thermal oil recovery processes undergo extreme temperature variation and this induces high thermal stresses in the casings. Therefore, forecasting the material behavior and checking for failure mechanisms becomes highly important. This paper uses Finite Element Methods to analyze the behavior two of the frequently used materials for casing - J55 and L80 steels. Modeling the casing and application of boundary conditions are performed through Ansys Workbench. Effect of steam injection pressure and temperature on the materials is presented in this work, indicating the possibilities of failure during heating cycle. The change in diameter of the casing body due to axial restriction is also presented. This paper aims to draw special attention towards the casing design in high temperature conditions of the well.

An Experimental Research on Enhanced Oil Recovery Using Local Polymers

2021 ◽  
Author(s):  
Abiola Oyatobo ◽  
Amalachukwu Muoghalu ◽  
Chinaza Ikeokwu ◽  
Wilson Ekpotu
Keyword(s):  
Enhanced Oil Recovery ◽  
Experimental Research ◽  
Oil Recovery ◽  
Capital Investment ◽  
Oil And Gas ◽  
Produced Water ◽  
Water Injection ◽  
Gum Arabic ◽  
Oil And Gas Industry ◽  
Profile Control

Abstract Ineffective methods of increasing oil recovery have been one of the challenges, whose solutions are constantly sought after in the oil and gas industry as the number of under-produced reservoirs increases daily. Water injection is the most extended technology to increase oil recovery, although excessive water production can pose huge damage ranging from the loss of the well to an increase in cost and capital investment requirement of surface facilities to handle the produced water. To mitigate these challenges and encourage the utilization of local contents, locally produced polymers were used in polymer flooding as an Enhanced Oil Recovery approach to increase the viscosity of the injected fluids for better profile control and reduce cost when compared with foreign polymers as floppan. Hence this experimental research was geared towards increasing the efficiency of oil displacement in sandstone reservoirs using locally sourced polymers in Nigeria and also compared the various polymers for optimum efficiency. Starch, Ewedu, and Gum Arabic were used in flooding an already obtained core samples and comparative analysis of this shows that starch yielded the highest recovery due to higher viscosity value as compared to Ewedu with the lowest mobility ratio to Gum Arabic. Finally, the concentration of Starch or Gum Arabic should be increased for optimum recovery.

scholarly journals Innovative Optical-Sensing Technology for the Online Fouling Characterization of Silicon Carbide Membranes during the Treatment of Oily Water

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 1161
Author(s):  
Mehrdad Ebrahimi ◽  
Axel A. Schmidt ◽  
Cagatay Kaplan ◽  
Oliver Schmitz ◽  
Peter Czermak
Keyword(s):  
Silicon Carbide ◽  
Oil Recovery ◽  
Oil And Gas ◽  
Produced Water ◽  
Cross Flow ◽  
Oil And Gas Industry ◽  
Ceramic Membranes ◽  
Transmembrane Pressure ◽  
Sensing Technology ◽  
Water Sensor

The oil and gas industry generates a large volume of contaminated water (produced water) which must be processed to recover oil before discharge. Here, we evaluated the performance and fouling behavior of commercial ceramic silicon carbide membranes in the treatment of oily wastewaters. In this context, microfiltration and ultrafiltration ceramic membranes were used for the separation of oil during the treatment of tank dewatering produced water and oily model solutions, respectively. We also tested a new online oil-in-water sensor (OMD-32) based on the principle of light scattering for the continuous measurement of oil concentrations in order to optimize the main filtration process parameters that determine membrane performance: the transmembrane pressure and cross-flow velocity. Using the OMD-32 sensor, the oil content of the feed, concentrate and permeate streams was measured continuously and fell within the range 0.0–200 parts per million (ppm) with a resolution of 1.0 ppm. The ceramic membranes achieved an oil-recovery efficiency of up to 98% with less than 1.0 ppm residual oil in the permeate stream, meeting environmental regulations for discharge in most areas.

Faster Convergence in Seismic History Matching by Dividing and Conquering the Unknowns

SPE Journal ◽  
2010 ◽  
Vol 15 (04) ◽  
pp. 1077-1088 ◽  
Author(s):  
F.. Sedighi ◽  
K.D.. D. Stephen
Keyword(s):  
Regression Analysis ◽  
Seismic Data ◽  
History Matching ◽  
Time Lapse ◽  
Business Decisions ◽  
Order Of Magnitude ◽  
Reservoir Simulation Model ◽  
The Uk ◽  
Pressure Changes ◽  
4D Seismic

Summary Seismic history matching is the process of modifying a reservoir simulation model to reproduce the observed production data in addition to information gained through time-lapse (4D) seismic data. The search for good predictions requires that many models be generated, particularly if there is an interaction between the properties that we change and their effect on the misfit to observed data. In this paper, we introduce a method of improving search efficiency by estimating such interactions and partitioning the set of unknowns into noninteracting subspaces. We use regression analysis to identify the subspaces, which are then searched separately but simultaneously with an adapted version of the quasiglobal stochastic neighborhood algorithm. We have applied this approach to the Schiehallion field, located on the UK continental shelf. The field model, supplied by the operator, contains a large number of barriers that affect flow at different times during production, and their transmissibilities are highly uncertain. We find that we can successfully represent the misfit function as a second-order polynomial dependent on changes in barrier transmissibility. First, this enables us to identify the most important barriers, and, second, we can modify their transmissibilities efficiently by searching subgroups of the parameter space. Once the regression analysis has been performed, we reduce the number of models required to find a good match by an order of magnitude. By using 4D seismic data to condition saturation and pressure changes in history matching effectively, we have gained a greater insight into reservoir behavior and have been able to predict flow more accurately with an efficient inversion tool. We can now determine unswept areas and make better business decisions.

Time-lapse seismic signal analysis for enhanced oil recovery at Cranfield CO2 sequestration site, Cranfield field, Mississippi

2013 ◽  
Vol 1 (2) ◽  
pp. T157-T166 ◽  
Author(s):  
Julie Ditkof ◽  
Eva Caspari ◽  
Roman Pevzner ◽  
Milovan Urosevic ◽  
Timothy A. Meckel ◽  
...  
Keyword(s):  
Oil Recovery ◽  
Time Lapse ◽  
Seismic Signal ◽  
Injection Well ◽  
Saturation Curve ◽  
Seismic Surveys ◽  
Seismic Amplitude ◽  
The Difference ◽  
Seismic Volumes ◽  
4D Seismic

The Cranfield field in southwest Mississippi has been under continuous [Formula: see text] injection by Denbury Onshore LLC since 2008. Two 3D seismic surveys were collected in 2007 and 2010. An initial 4D seismic response was characterized after three years of injection, where more than three million tons of [Formula: see text] remain in the subsurface. This interpretation showed coherent seismic amplitude anomalies in some areas that received large amounts of [Formula: see text] but not in others. To understand these effects better, we performed Gassmann substitution modeling at two wells: the 31F-2 observation well and the 28-1 injection well. We aimed to predict a postinjection saturation curve and acoustic impedance (AI) change through the reservoir. Seismic volumes were cross-equalized, well ties to seismic were performed, and AI inversions were subsequently carried out. Inversion results showed that the change in AI is higher than Gassmann substitution predicted for the 28-1 injection well. The time-lapse AI difference predicted by the inversion is similar in magnitude to the difference inferred from a time delay along a marker horizon below the reservoir.

Sign in / Sign up

Export Citation Format

Share Document