sentence-transformers How to use Sampath1987/EnergyEmbed-1E with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("Sampath1987/EnergyEmbed-1E", trust_remote_code=True)
sentences = [
"How does vendor-specific data acquisition affect DTS profile interpretation?",
"Bridging data management gap by gathering all well integrity data in one unique data base. The aim of ADNOC Offshore in-house Well Integrity Data Management System (WIDMS) is to comply with the 3A rule: Accessibility of the data, Accuracy by performing regular quality check and Analysis. The analysis allows to maintain wells barriers robust, to ensure personnel safety and to quickly identify integrity issues to make qualified decisions about appropriate mitigations measures and avoid risk escalation. WIDMS has been developed in-house with inputs and collaboration of various stake holders. An enhancement list has been established selecting the most relevant features that will be added value to the system. Therefore, Automation for sub processes like thresholds calculations and Risk Assessment which gives input for Well Passports that contains all the required information to evaluate the well risks and implement the required mitigation measures.\nEnd users are following a RACI Chart to keep WIDMS database on track and to ensure no data falls through the cracks as all the data workflow is defined through the different steps such as providing data, entering it in the system, informing relevant stakeholders and providing technical clarifications if needed. The result of data acquisition in WIDMS is that data flows across the entire organization, with defined access rights in line with ADNOC Offshore policies. This data is collected from various sources, is a robust data base, essential for evaluating and maintaining well integrity.\nIt is enhancing well barriers system management by allowing to have full overview of well's barriers performance. Moreover, it allows to have reliable and continuously available data such as annulus pressure data that is critical for well integrity assurance, to avoid the uncontrolled release of hydrocarbons to the atmosphere. Notifications have been implemented so alerts can be sent for engineers to inform about any abnormality and non-compliance. As technology evolves, using paper-based processes, excel spreadsheets, time-based equipment inspection and testing become less effective. Well diagnostics are expensive so utilizing well data analytics through this digital hub project will ease having detailed real time data and quick analysis for early detection of failures and anticipation and reduction of risk escalation.",
"##### 2.3.1 Site characterization - secondary seal \nSecondary seals might have a significant relevance in ensuring CO 2 containment, acting\nas additional barrier to flow, although it is not clear if it is considered a requirement for\nstandards. Two documents show some contradiction: \nISO 27914 [36] is silent on secondary seal as a requirement until section 5.4.3.2 that describes\nits characterization. Moreover, if it is a requirement, characterization should include not\nonly geometry and lithology, but also integrity evaluation, which is not mentioned. \nISO/TR 27915 [37] section 5.2.6 and Figure 2 state that the geological storage complex is\ncomposed of the reservoirs where CO 2 is injected and the caprock (or seals); it then states\nthat additional geologic layers are outside complex.",
"Geothermal energy is considered a reliable, sustainable and abundant source of energy with minimized environmental impact. The extracted geothermal energy may be utilized for direct heating, or electricity generation. The main challenge to access this energy is tremendous capital expenditures required for drilling and completion. Therefore, this work discusses and evaluates retrofitting abandoned petroleum wells to geothermal as a commonly proposed solution to the mentioned challenge.\nThere are many oil and gas wells globally which are not used for production, injection or other purposes. Well abandonment is commonly considered as an essential measure to ensure safety and integrity of these wells, bearing huge costs and concerns for the petroleum industry. By converting abandoned or non-activated oil and gas wells to geothermal wells, it is claimed to be possible to produce geothermal energy and generate power. As a crucial stage for the claim verification and evaluation of feasibility or efficiency of this conversion, it is important to be aware of the practical and simulation case studies.\nTherefore, in this work, this work presents a comprehensive overview and analysis of 20 case studies published from different countries, followed by important downhole and surface parameters. As for the downhole characteristics, production scenarios either open-loop or closed-loop, optimization of open-loop systems, borehole heat exchangers with their different types and dimensions, and insulations are covered. Next, surface cycles including organic Rankine cycle (ORCs), selection of circulation fluids, flow rates, and working fluids are covered, followed by produced and net powers with evaluation of coefficient of performance (COP) and thermal efficiency. This investigation shows there is good potential for producing geothermal energy from abandoned and non-activated petroleum wells."
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4] 
