Use of diverters for altering fluid distribution among created hydraulic fractures in horizontal wells has gained popularity in recent years, both for initial and re-fracturing treatments. Aims in initial fracturing treatments have included creating more uniform distribution of slurry within the created fractures, increasing stage efficiency by reducing the number of pumping stages while increasing the number of clusters per stage, increasing the number of fractures created in openhole completions, reducing interactions between fractures in adjacent horizontal wells, etc. In re-fracturing treatments, a popular application is for altering fluid distribution in wells re-treated without isolation between stages (Pump & Pray/Bullheading) with the intent of increasing the number of re-activated fractures and initiating new fractures through added perforations.
Engineering analysis of the mechanics of fluid diversion has not received the same degree of attention as its use. The reported discussions are often limited in their scope, two-dimensional in structure, and somewhat speculative in their conclusions.
This paper divides the targets of diversion into three categories; at the wellbore/perfs, near wellbore, and deeper inside the fracture. It divides the types of diverters into three categories, mechanical, solid particulate (including proppants), and chemical. The applications are divided into two categories, initial and re-fracturing, together with highlighting their differences and requirements for successful diversion. The paper discusses how presence of proppant changes the fluid distribution in favor of more conductive perforations. It considers the fracture as a three-dimensional structure, extending on both sides of the wellbore. It describes how different diverting agents cause fluid redistribution between the fractures, and the important role of proppant in some applications. It shows that as the target of fluid diversion moves away from the wellbore the chances of its success become smaller and more unpredictable, while also the time before effective diversion takes place becomes longer.
Comprehensive understanding of the mechanics of fluid diversion helps in the selection of the type of diverter and how best to deploy it for achieving specific objectives and results.
The paper provides a technical overview of an operator's Real-Time Drilling (RTD) ecosystem currently developed and deployed to all US Onshore and Deepwater Gulf of Mexico rigs. It also shares best practices with the industry through the journey of building the RTD solution: first designing and building the initial analytics system, then addressing significant challenges the system faces (these challenges should be common in drilling industry, especially for operators), next enhancing the system from lessons learned, and lastly, finalizing a fully integrated and functional ecosystem to provide a one-stop solution to end users.
The RTD ecosystem consists of four subsystems as shown in architecture
RTD ecosystem architecture
RTD ecosystem architecture
All of these subsystems are fully integrated and interact with each other to function as one system, providing a one-stop solution for real-time drilling optimization and monitoring. This RTD ecosystem has become a powerful decision support tool for the drilling operations team. While it was a significant effort, the long term operational and engineering benefits to operators designing such a real-time drilling analytics ecosystem far outweighs the cost and provides a solid foundation to continue pushing the historical limitations of drilling workflow and operational efficiency during this period of rapid digital transformation in the industry.
Potapenko, Dmitriy (Schlumberger) | Theuveny, Bertrand (Schlumberger) | Williams, Ryan (Schlumberger) | Moncada, Katharine (Schlumberger) | Campos, Mario (Schlumberger) | Spesivtsev, Pavel (Schlumberger) | Willberg, Dean (Schlumberger)
Highly efficient multi-stage hydraulic fractured horizontal wellbores are the dominant completion method for many basins worldwide. One potential weakness of multi-stage hydraulic fracturing is that the later stages of the completion workflow – frac-plug drill out (FPDO) and flowback – cause large pressure fluctuations and transient flows through the perforation clusters that coincide with a period of low closure stress in the fractures. The proppant packs in the fractures during this period are fragile and prone to failure. Previously reported results show that flowback and initial production practices have a major impact on proppant production, maintenance and disposal costs and the subsequent well performance. In this paper the results from over 200 FPDO and flowback operations from the United States and Argentina are reviewed. These results show that maintaining a balanced flowrate during FPDO operations is critical for minimizing inadvertent damage to the hydraulic fracture network.
The FPDO flowrate balance is the difference between the coiled tubing injection and annular return flowrates. The magnitude and sign of the balance corresponds to the instantaneous flowrate through the open perforation clusters into or out of the hydraulic fracture network. A positive balance rate, or overbalance, injects fluid into the fracture system. A negative balance rate, or underbalance, produces stimulation or formation fluids from the fracture network. Sudden changes between these two regimes creates local flows that can be severe enough to flush large quantities of proppant out of the fractures. Our results show that high-frequency multiphase flowmeters simplify the process of maintaining balance (no inflow, no outflow). Furthermore, close monitoring of any imbalance that develops, and rapid control of the surface choke and injection rate, can provide for an efficient operation while protecting the integrity of the fracture system.
Early monitoring of flowback and production with a high frequency flowmeter was shown to be extremely useful technique for optimizing well productivity during well clean-up. This paper also shows how a dual energy gamma ray multiphase flowmeter successfully quantified proppant produced during FPDO and flowback. Examples of the dynamics of sand production are shown, as well as correlations to events of excessive underbalance conditions.
At the end of the paper we show that most of the highlighted problems can be solved through making changes to the well construction workflow and accounting for relationships between various well operations. Incorporation of this workflow enables early prediction of well performance issues and their efficient resolution.
Hydrocarbon production from shale formation has become an essential part of the global energy supply in the past decade. The life of a project in an unconventional play significantly depends on the prediction of Estimated Ultimate Recovery (EUR). However, the conventional methodology to predict EUR becomes less accurate for shale formations, which significantly affects the economics returns of projects in unconventional plays. The objective of this article is to investigate the most important independent variables, including petrophysics and completion parameters, to estimate EUR by the machine learning algorithm. A novel machine learning model based on Random Forest Regression is introduced to predict EUR and to rank the importance of the independent variables.
In this article, production/petrophysics/engineering/ data with more than 25 variables from 4000 wells in Eagle Ford is summarized for analysis. The data is collected from production monitoring, well logging, well testing, seismic interpretation and lab experiments. This paper has three major components. Firstly, a multivariate linear regression model is created to predict the overall EUR. Secondly, the spatial autocorrelation analysis is carried out to identify whether spatial variables could affect the accuracy of the multivariate regression model. Thirdly, the Random Forest Regression models are trained to examine their reliability in predicting EUR with spatially autocorrelated data. The importance of key predictors is also identified. The final models are tuned with optimized hyperparameters. Through the article, the predictive capabilities of each Random Forest Regression model are discussed in detail to understand the physics behind unconventional hydrocarbon production mechanisms.
The results and workflow presented in this paper are insightful and novel. Firstly, we test the multivariate regression analysis with all the petrophysics and completion variables using the backward elimination method. This widely used model has a limitation of excluding the spatial information. In order to identify the impact of spatial variable, we calculate the Moran's Index and find out that the data in this study is clustered or spatially autocorrelated. The p-value for EUR, Oil EUR and Gas EUR are 0.000002, 0.000000 and 0.12, which all reject the null hypothesis that the data is randomly distributed. To include the spatial information in the prediction, we use advanced machine learning technology, Random Forest, to predict the EUR with a combination of petrophysics, completion variables and spatial information. The key variables to predict EUR, Oil EUR and Gas EUR by the Random Forest Regression are identified. However, the importance of the key variables to predict Oil EUR and Gas EUR are different. Therefore, we split the overall EUR Random Forest Regression model (57% explained) into two prediction models, one for Oil EUR prediction and one for Gas EUR prediction. The Gas EUR Random Forest Regression model has better performance (76% explained) compared to the Oil EUR Random Forest Regression model (60% explained).
This study provides a deeper understanding of unconventional hydrocarbon production prediction from a big data perspective, and proposes a novel and reliable machine-learning model to predict EUR to evaluate economic returns in Eagle Ford. Compared to the traditional multivariate regression model, our Random Forest Regression models are more reliable. In addition, the Random Forest technique is able to rank the importance of the relevant independent variables, and the rank of importance can be applied to guide and to improve data collection and model training for further study on this topic. The workflow presented in this article can be also used to train data for other unconventional resource plays.
This seminar will teach participants how to identify, evaluate, and quantify risk and uncertainty in everyday oil and gas economic situations. It reviews the development of pragmatic tools, methods, and understandings for professionals that are applicable to companies of all sizes. The seminar also briefly reviews statistics, the relationship between risk and return, and hedging and future markets. Strategic thinking and planning are key elements in an organisation’s journey to maximise value to shareholders, customers, and employees. Through this workshop, attendees will go through the different processes involved in strategic planning including the elements of organisational SWOT, business scenario and options development, elaboration of strategic options and communication to stakeholders.
Digital technologies serve as a primary theme of this year’s group, with a few environmentally conscious firms included in the mix. The well will immediately be brought on production and is expected to flow at more than 100 MMscf/D of gas and 3,000 B/D of associated condensate, the company said. The main goal of production logging is to evaluate the well or reservoir performance. The shale sector is studying the results of a 23-well experiment in the southeastern corner of New Mexico to learn what the wider implications might be. The shale sector is making moves to consolidate amid investor pressure to increase cash flow.
Underbalanced coiled tubing drilling has continually advanced since the first trials in the 1990s but remains a relatively niche drilling technology. With UBCTD projects set to start in many countries next year, this technology may be seeing a turning point. Considering most of the rigs deal with human-machine interface systems, the role of human factors is at the heart of any successful operation. Eye-tracking technology can be useful in real-time operation centers where ocular movement data can improve the professionals’ performance. For 60% of Sub-Saharan Africa and South Asia, by cultivated land area, an acute challenge is access to water.
Mitigation of stress shadowing could significantly enhance the impact of hydraulic fracturing treatments, increasing stimulated reservoir volume and leading to higher production of hydrocarbons. More than a decade ago, perforation cluster spacing was designed up to 700 ft in Barnett and Bakken plays. Today, the spacing is as close as 15 ft apart in Eagle Ford and DJ Basin and operators are optimizing fracture spacing for achieving higher initial production rates.
The main goal of production logging is to evaluate the well or reservoir performance. The Delaware Basin presented a challenging scenario for Anadarko due to the company’s tankless development approach. Sand filtration was identified as a perfect fit for this application. Natural gas hydrates are considered to store vast amount of natural gas trapped in the subsurface worldwide. However, gas hydrates are yet to be commercialized due to technical challenges in the production technology.
The Powder River Basin has emerged over the past year as the latest source of oil production growth for the Lower 48. Companies ranging from a reborn Samson Resources to US onshore mainstays Devon, Chesapeake, and EOG are now betting on the basin to become a long-term core asset. Colorado’s industry lacks the size, variety, and Wild West characteristics of Texas, but that is precisely why the Centennial State’s oil production is surging to record levels. This paper describes a comprehensive field study of eight horizontal wells deployed in the stacked Niobrara and Codell reservoirs in the Wattenberg Field (Denver-Julesburg Basin).