EnergyEmbed-v2 / README.md

Sampath1987

fine-tuned EnergyEmbed-v2 2 epochs

438976f verified about 2 months ago

preview code

raw

history blame contribute delete

73.2 kB

metadata

tags:
  - sentence-transformers
  - sentence-similarity
  - feature-extraction
  - dense
  - generated_from_trainer
  - dataset_size:89129
  - loss:MultipleNegativesRankingLoss
base_model: Alibaba-NLP/gte-multilingual-base
widget:
  - source_sentence: >-
      How does vendor-specific data acquisition affect DTS profile
      interpretation?
    sentences:
      - >-
        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.

        End 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.

        It 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  

        Secondary seals might have a significant relevance in ensuring CO 2
        containment, acting

        as additional barrier to flow, although it is not clear if it is
        considered a requirement for

        standards. Two documents show some contradiction:  

        ISO 27914 [36] is silent on secondary seal as a requirement until
        section 5.4.3.2 that describes

        its characterization. Moreover, if it is a requirement, characterization
        should include not

        only geometry and lithology, but also integrity evaluation, which is not
        mentioned.  

        ISO/TR 27915 [37] section 5.2.6 and Figure 2 state that the geological
        storage complex is

        composed of the reservoirs where CO 2 is injected and the caprock (or
        seals); it then states

        that 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.

        There 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.

        Therefore, 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.
  - source_sentence: >-
      Why must welding consumables be limited to specific classifications and
      manufacturers for EGW?
    sentences:
      - >-
        8 API R ECOMMENDED P RACTICE 582  

        **5.2.6 EGW**  

        The use of EGW shall be limited by the following conditions:  

        a) EGW shall be used only with filler materials specifically intended
        for the EGW process (ASME/AWS SFA/A5.26/

        SFA/A5.26M),  

        b) welding consumables shall be limited to the classification and the
        manufacturer’s trade name used in the PQR,  

        c) only filler materials having classifications with specified minimum
        impact test requirements should be used.  

        **5.2.7 SAW**  

        **5.2.7.1** SAW procedures shall be requalified whenever the welding
        flux is changed from one manufacturer’s trade

        name to another. Equivalence under ASME _BPVC_ Section II, Part C, or
        AWS filler metal specifications shall not be

        considered adequate for substitution without requalification.  

        COMMENTARY It is recognized that fluxes having the same classification
        can be very different in their

        composition. However, nominal flux composition is not included in AWS or
        ASME specifications/codes, and flux

        suppliers do not normally provide this information. Differences among
        fluxes of the same classification can result in

        different and unanticipated weld properties when these fluxes are used
        interchangeably over the range of variables

        typically stated in weld procedure specifications.  

        **5.2.7.2** Manually held (semiautomatic) SAW is not permitted for
        welding pressure-containing parts, unless approved

        by the purchaser.  

        **5.2.7.3** A separate qualification is required for SAW welds in which
        any pass is greater than [1] / 2 in.  

        **5.3 Single-sided Welded Joints**  

        For single-sided welded joints where process side corrosion is a
        concern, welding processes using coatings or fluxes

        shall not be used for root pass welding of austenitic stainless steels,
        non-ferrous alloys and nickel-base alloys unless

        slag can be removed from the process side of root passes and the area
        inspected for slag removal.  

        **5.4 Combining Welding Processes**  

        Combining two or more welding processes that use alloy filler metals of
        different nominal compositions, other than A1

        thro ~~ug~~ h A5, requires qualification as a combination procedure.
      - >-
        Following multi-disciplinary reviews, an opportunity was identified to
        restore production and unlock incremental reserves from well X, a dual
        completion in two different reservoirs but subsequently deserted due to
        long term community crisis that led to over 25years of non-production
        with complete vandalization of well head and flowlines.

        The method employed involved the strategic resolution of long-term
        crisis between two communities where well X is located, via a
        multi-disciplinary effort involving the operating company’s Community
        Relations, HSSE, Production Engineering, Operations Support and
        Portfolio Management functions. The installation of a retrofitted well
        head was done with first line and second line maintenance carried out.
        Wireline drifting and static bottom hole pressures were acquired for
        both strings using slickline equipment and a preliminary well test was
        conducted for both strings with production to a flowback tank.

        The preliminary result for the long string (LS) indicated a high water
        cut (>80%), while the result from short string (SS) was in line with
        expectation (<57%). The test result from the short string informed the
        decision to construct a new flowline for restoring its production, while
        further subsurface evaluation is required for the long string (LS). The
        significance of the short string (SS) result is the unlocking of
        additional reserves ca. 1.0MMSTB from a reservoir with remaining oil in
        place estimated at ca. 18MMSTB, where the short string (SS) is the only
        drainage point currently completed on the reservoir.

        This solution provides a cost effective and efficient way to increasing
        production and reserves at minimal expenditure leveraging on
        multi-disciplinary expertise, using existing infrastructures as well as
        resolving community crisis, where applicable.
      - >-
        **Exploration & Production**  

        **General Specification** Date: 10/2007  

        **GS EP STR 301** Rev: 07  

        successful practice of the process in previous similar jobs to the
        satisfaction of the

        COMPANY.  

        b) Only Extra Low Hydrogen processes (max. 5 ml H2/100 g) shall be used
        for welding and tack  

        welding of Special and First Category members or materials having
        specified YS above

        262 MPa (38,000 psi). The same requirement shall apply for any welding
        on castings and

        forgings.  

        c) For Second Category members and Non-Structural members, welding
        processes other than

        Extra Low Hydrogen processes may be used, subject to prior approval by
        COMPANY, for

        materials having specified YS up to 262 MPa together with thickness up
        to 12.70 mm

        (0.500”).  

        d) The number of different welding processes shall be minimized.  

        e) Different welding consumables qualities (basic extra low, basic low,)
        in a same type of

        consumables shall be avoided.  

        **8.5 Welding consumables**  

        **8.5.1 Selection of consumables**  

        a) Consumables shall conform to ANSI/AWS D 1.1 code and shall have been
        approved by an

        international recognized certification body (e.g. DNV, LLOYD’s, etc.).  

        b) If classification of the structure is required, welding consumables
        shall conform to rules of the

        Classification Society.  

        c) Cellulosic electrodes are strictly forbidden for structural use  

        d) Welds forming connections between steels of different grades of
        material shall develop the

        minimum specified tensile properties of the lower steel grades being
        joined, unless otherwise

        previously approved by the COMPANY.  

        Welds forming connections between steels of different grades of material
        shall develop the

        minimum specified notch impact properties at the lowest temperature of
        steel grades being

        joined, unless otherwise previously approved by the COMPANY.  

        e) For repair welding or multiple repairs, “extra low hydrogen”
        electrodes are required

        (i.e. maximum specified hydrogen content of 5 ml per 100 gram of weld
        metal).  

        f) For welding castings or forgings, “extra low hydrogen” electrodes are
        required (i.e. maximum

        specified hydrogen content of 5 ml per 100 gram of weld metal).
  - source_sentence: >-
      What is the recommended use of blank samples in sampling procedures
      involving the trapping or precipitation of components?
    sentences:
      - >-
        elements. We do this by performing a similarity transformation on the
        matrix _k_ . The coordinate systems _x_ = { _x_ 1, _x_ 2 } and _y_ = {
        _y_ 1,, _y_ 2 } are related by the similarity transformation matrix  

        _A_ such that  

        _y_ = _Ax_ .
        ................................................................
        (2.127)  

        The two coordinate systems are shown in Fig. 2.6.

        An angle ( _θ_ ) is associated with the transformation in Eq. 2.127 by
        writing the 2D coordinate transformation as  

        _y_ 1  

        _y_ 2  

        _x_ 1  

        _x_ 2  

        =  

        cos _θ_ sin _θ_  

        −sin _θ_ cos _θ_  

        . ........................................... (2.128)  

        The coordinate systems _x_ = { _x_ 1, _x_ 2 } and _y_ = { _y_ 1,, _y_ 2
        } are related by the counterclockwise rotation shown in Fig. 2.6. We
        have an aligned coordinate system _y_ = { _y_ 1,, _y_ 2 } with the

        principal axes of the permeability tensor. The diagonal tensor in the
        coordinate system  

        _y_ = { _y_ 1,, _y_ 2 } has the form  

        _k_ ′=

        (  

        _k_ max 0  

        0 _k_ _T_

        ) [, .........................................................
        (2.129)]  

        **Print** **Search** **Chapter 1** **Home** **Chapter 3** **Bookmarks**
        **Help**
      - >-
        **© 2010 COPYRIGHT MERCADO NEGRO, LAS PLAYITAS. MARACAIBO-EDO. ZULIA,
        VENEZUELA.**  

        **PARA COMPRAR AL DETAL O AL MAYOR, ESTE Y OTROS PRODUCTOS, FAVOR
        PREGUNTAR POR EL GÖAJIRO BLANCO, EN EL MERCADO LAS PLAYITAS.**  

        **ADVERTENCIA: "EL DERECHO DE AUTOR NO ES UNA FORMA DE PROPIEDAD SINO UN
        DERECHO CULTURAL. EXIGE TU DERECHO"**  

        I-208 Petroleum Engineering Handbook—Vol. I  

        **Fig. 4.10—Chromatogram showing broad OBM peak.**  

        **Fig. 4.11—Chromatogram showing narrow OBM peak.**  

        Special correction techniques are increasingly used within the oil
        industry, and because

        these techniques vary between organizations and laboratories, sample
        selection should be done

        only after considering which method to use. Many companies are forced to
        use oil-based

        drilling muds to manage drilling costs in water-sensitive formations,
        and the added expense of

        handling contaminated samples (and the risk associated with
        poorer-quality data) must be used

        to evaluate the overall economic balance.  

        For water samples, comparisons of duplicates also give a good indication
        of quality. Where

        fluid concentration may be stabilizing (e.g., at the end of a cleanup),
        sequential samples should

        be used to look for compositional trends and thus to help decide if
        representative fluid has

        been sampled. For some sampling procedures involving trapping or
        precipitation of particular

        components, it is highly recommended to use blank “samples,” which
        undergo exactly the

        same treatment and storage as the actual sample and provide a reference
        measurement to assist

        with the interpretation of laboratory measurements. More details are
        available in API _RP 45._ [10]  

        **Print** **Search** **Chapter 3** **Home** **Chapter 5** **Bookmarks**
        **Help**
      - >-
        the ideal time to take samples? (6) Will on-site analyses be required?
        (7) Who will perform

        sampling and analysis duties?

        Fluid-sampling operations are often left to service-company personnel,
        but because significant variation in levels of competence exists within
        the industry and within service companies

        themselves, it is recommended either to use specialist laboratory
        personnel or to supervise the

        service-company operations closely.

        General guidelines for choosing reservoir-fluid-sampling methods and
        sample quantities required are summarized in **Table 4.2.** Regardless
        of the actual volumes mentioned, you should

        collect at least two separate samples of each fluid, referred to as
        duplicate or replicate samples.

        This reduces the chance of losing information if one of the samples
        leaks or is accidentally

        damaged during laboratory operations, and it allows a comparison between
        the samples as part

        of the quality-control procedures.

        Surface-separator sampling is the most common technique, but the
        reservoir-fluid sample

        recombined in the laboratory is subject to errors in the measured GOR
        and any imprecision in

        the laboratory recombination procedure. Downhole samples (or wellhead
        samples) are not affected by such inaccuracies but require the fluid to
        be in monophasic condition when sampled;

        this can be confirmed definitively only afterward in the laboratory.
        Also, there is general reluctance to attempt downhole sampling in
        gas/condensate reservoirs because many are saturated,

        and the phases are likely to segregate in the wellbore. The ideal
        situation for a laboratory is to

        receive both surface and downhole samples because a choice is then
        available, and a good idea

        can be obtained of how representative the resulting fluid is.

        In certain circumstances, it can be good practice to collect “backup”
        fluid samples at the

        earliest opportunity during a production test, even if a well has not
        cleaned up properly. If the

        test has to be aborted for some reason [well bridging, unexpected levels
        of hydrogen sulfide

        (H 2 S), etc.], the backup samples may be of great value, even if they
        are not 100% representative. If the test is completed successfully, the
        backup samples can be discarded to avoid the

        cost of unnecessary shipment and testing.

        If sampling is part of a long-term monitoring program, such as those
        required by government authorities or those forming part of
        custody-transfer contracts, the methods defined in the

        appropriate documentation or contracts must be followed as closely as
        possible, even if this
  - source_sentence: >-
      What is the significance of implementing a centralized, web-based
      integrated surveillance tool for production optimization?
    sentences:
      - >-
        P RESSURE                - RELIEVING AND D EPRESSURING S YSTEMS 141  

        **5.7.11.2.3 Flare Gas Characteristics**  

        Flare gases can have widely varying compositions that shall be evaluated
        during specification of recovery systems.

        The potential for materials that are not compatible with the flare gas
        treating systems or ultimate destinations shall be

        determined. For example, relief streams containing acid gases typically
        are routed directly to the flare, thereby

        bypassing the recovery system. Highly inert streams can also be
        incompatible with recovery systems.  

        **5.7.11.3 Design Considerations**  

        **5.7.11.3.1 Sizing**  

        Figure 13 shows a conceptual design for a flare gas recovery system.
        Typically, the system consists of one or more

        reciprocating compressors whose suction is directly connected to the
        flare header. The compressed gas is usually

        routed to some type of treating system appropriate for the gas
        composition, then to fuel gas or processing systems.  

        3  

        **Key**

        1 compressor load control

        2 flare gas treating

        3 from process unit flare knockout drums  

        4 flare header  

        5 flare knockout drum (if used)  

        6 water seal  

        7 flare  

        a Compressor shutdown.  

        **Figure 13—Typical Flare Gas Recovery System**  

        Copyright American Petroleum Institute

        Provided by IHS under license with API Licensee=Petrofac International
        Ltd/5954785001, User=McNicol, William

        No reproduction or networking permitted without license from IHS Not for
        Resale, 01/29/2014 03:10:03 MST
      - >-
        Inorganic scale precipitation and deposition in oil and gas wells can
        cause significant production loss, which results in additional
        operational expenditure (OPEX) and health safety and environmental (HSE)
        risks. Scale management requires a detailed understanding of production
        rates, hydrocarbon and produced water compositions as well as reservoir
        conditions. Accurate real-time analysis of produced water compositions
        can immediately identifiy scaling risks in a production well and can
        lead to significantly reduced production loss, optimized chemical
        dosages, and fewer workovers, consequently lowering OPEX and mitigating
        HSE risk. This paper introduces development of a device capable of
        measuring the most critical parameters associated with inorganic scale
        in flowing produced water including pH, alkalinity, strontium, barium,
        sulfate, total hardness, total dissolve solids (TDS) and others.

        In order to measure these water properties with the device, different
        methods were tested, but eventually, a combination of spectrophotometric
        and other methods were determined effective. One of the challenges of
        using spectrophotometric methods is the reagent stability over time.
        Hence, customized reagents were prepared for this application and the
        stability of these reagents was tested over time. Specific calibration
        methods were designed in order to extend the usage of the reagents.

        Static measurements were initially performed and the results showed
        precise measurements of all the parameters. Results from dynamic tests
        utilizing real time flow and static test were in agreement and the
        accuracy was confirmed by traditional methods. Once the device prototype
        was built in our laboratories, production fluids were used to test the
        complete device. This device can be placed at various attachment points
        from the wellhead to the separator. This automated device is capable of
        collecting a discrete production fluid sample, separating produced water
        from the bulk phase and measuring various properties of produced water.
        These properties are reported electronically and used as part of a
        combined real time scale risk prevention system. In addition, this
        device measures parameters while maintaining wellhead pressure and
        temperature in order to eliminate the potentials errors in measurements,
        for instance pH of water changes due to degassing and precipitation as a
        result of changes in pressure and temperature.

        A field trial is planned to test the device under full flowing
        conditions. This will be the first automated real-time produced water
        composition monitoring device with high measurement accuracy while
        maintaining pressure and temperature of samples, which can be attached
        at various points from wellhead to separator. This can be beneficial to
        identify the scaling risk in production wells before severe scaling
        occurs. The device is designed to enhance reliability of water
        properties measurements, provide real-time measurements, and reduce
        downtime and costs associated with scale problems and sampling.
      - >-
        In 2009, the Kuwait Integrated Digital Field (KwIDF) project was
        established in the Sabriyah field in north Kuwait to boost production
        and reserves (Al-Jasmi et al. 2014). The goal was to help realize the
        vision of sustained oil production in Kuwait of four million barrels of
        oil equivalent per day (BOE/D) by 2030 (Goel et al. 2013). The project
        involved the creation of 11 integrated, automated workflows, and a
        real-time collaborative environment to help optimize production, reduce
        downtime, and improve reservoir management:

        Key performance monitoring—calculates and displays key parameters to
        monitor and assess asset performance at the field and well levels
        (Al-Jasmi et al. 2013).

        Well performance evaluation (WPE)—allows users to model and evaluate any
        well in real time, from completion face to wellhead (Cullick et al.
        2013).

        Smart production surveillance (SPS)—helps enable users to control
        production and make surveillance decisions in real time (Villamizar et
        al. 2013).

        Production loss—an advance workflow for users to compare current oil
        production to pre-established allowable rates (Villamizar et al. 2013).

        Electric submersible pump (ESP) diagnostic and optimization—helps enable
        users to interactively monitor and optimize ESP operated well operations
        (Velasquez et al. 2013).

        Production allocation—integrates the allocation process within the KwIDF
        environment, increases the frequency of the allocation cycle, and
        improves the accuracy of allocated volumes (Al-Jasmi et al. 2013).

        Gas lift (GL) diagnostic and optimization—uses a smart real-time control
        that provided proactive recommendations for GL systems optimization
        (Al-Jasmi et al. 2013).

        Reporting and distribution—displays system generated alarms from all
        KwIDF workflows, generates tickets, and reports ticket status (Al-Jasmi
        et al. 2013).

        Simulation model update and ranking—an automated workflow for reservoir
        history matching (Carvajal et al. 2013).

        Reservoir visualization and analysis, and subsurface waterflood
        optimizer—helps enable the monitoring of subsurface health during the
        waterflooding process, and provides predictive reservoir optimization
        analysis and actions (Ranjan et al. 2013).

        By 2012, KwIDF had been deployed on 49 wells, representing a pilot that
        served as a proof of concept. By 2013, cumulative production gains of
        756,000 barrels of oil were reported (Singh et al. 2013). While the
        gains were impressive, and management wanted to expand KwIDF, it was
        recognized that full deployment would pose significant challenges and,
        without a set of necessary changes, the value of KwIDF would not be
        realized.

        The key challenge facing management was to identify the appropriate
        operating model to deliver on the KwIDF vision and scale the program to
        accommodate future expansion across the rest of the organization. A
        transition and deployment assessment team was established by management
        to address this challenge.

        The transition and deployment assessment project produced a recommended
        operating model, a transition road map, change management strategy, risk
        and mitigation plan, and project charters to assist the program team and
        steering group in the deployment of KwIDF across the rest of North
        Kuwait.
  - source_sentence: >-
      What role did anti-collision analysis play in the drilling of the dual
      lateral well?
    sentences:
      - >-
        This paper aims to analyze the impact of appraising and developing
        marginal fields with multiple stacked reservoirs which is quite
        challenging in terms of techno commercial value. The development of such
        marginal reservoirs using conventional single horizontal wells drilling
        and completion is uneconomical. Therefore, it was necessary to engineer
        a solution that can enhance the commercial value of the project by
        reducing CAPEX and OPEX. This paper will present the first comprehensive
        business case, where multiple stacked reservoirs with marginal reserves
        were studied to produce independently using multilateral completions,
        granting full accessibility of the laterals while achieving production
        monitoring and reservoir surveillance.
      - >-
        This paper is a comprehensive analytic driven study on the use and
        sizing of membrane filters to improve the injected water quality for
        maintaining injectivity in tight carbonate reservoirs. Out of the
        different mechanisms of formation damage, the pore plugging with the
        migration of particles within the injectant fluids by bridging at the
        pore throat junctions and/or by pore filling can lead to the buildup of
        an internal filter cake away from the wellbore that limits the well’s
        injectivity and can affect the vertical and lateral sweep.

        This type of formation damage is very difficult to treat with any kind
        of stimulation and the impact will be manifested especially in tight
        formations with interbedded stylolites layers with a total range of
        permeabilities from 2 to less than 1 milli-Darcy and a median pore
        throat size ranging from 2.5 to 0.3 micron meters. The study comprises
        several parts starting with a geological analysis that was conducted to
        identify areas and layers most prone to formation pore plugging by
        analyzing thin-sections and MICP data. Second, in the lack of core flood
        tests, a reservoir and well study analyzed existing water injectors
        situated in similar or slightly higher quality rock areas through the
        analysis of injectivity index behavior to estimate the impact of damage
        and the expected injector’s half-life.

        As a result, through the application of an analytical mathematical model
        for defining deep bed filtration parameter, a correlation was
        established based on average injected particle size and reservoir rock
        quality to aid in selecting the proper water injection filter size. In
        order to confirm that, a dedicated injectivity test in a horizontal well
        utilizing membrane filters was carried out to assess eventual formation
        damage and the filters efficiency by conducting a series of multiple
        pressure fall-off tests coupled with injection profile logging to
        monitor any induced damage within the wellbore region.

        Finally, the operational aspects and the integration within field
        development plans were addressed, especially with the recommended well
        placement and completion. This culminated in a field development
        strategy for formation damage mitigation in tight carbonate reservoirs
        during production and injection phase that can be used in other similar
        fields.
      - >-
        The most common challenge in horizontal drilling is depth uncertainty
        which can be due to poor seismic data or interpretation. It is arguable
        that a successful landing of the wellbore in the reservoir optimally and
        within the desired zone is the most challenging in most geosteering
        operation. The presence of fluid contacts such as oil-water-contact
        (OWC) and gas-oil-contact (GOC) complicates the whole drilling process,
        most especially if these fluid contacts are not well defined or known.
        Additionally, the ability to map the boundaries of the reservoir as the
        BHA drills the lateral section is an added advantage to remaining within
        the desired reservoir section.

        The success of any reservoir navigation service where seismic
        uncertainty at the reservoir top is high will rely largely on how
        effective the geosteering system is and how the geosteering engineer is
        able to react promptly to changes while landing the well in the
        reservoir and drilling the lateral section with without exiting the
        reservoir.

        Reservoir Navigation Service (RNS) provides the means for the drilling
        near horizontal or horizontal wells for the purpose of increasing
        hydrocarbon extraction from the earth's subsurface. This involves the
        use of a pre-defined bottom hole assembly (BHA) with inbuilt downhole
        logging while drilling (LWD) and measurement while drilling (MWD)
        sensors. The measurements from these downhole sensors are uplinked to
        the surface of the wellbore where they are converted to meaningful
        petrophysical data. The goal is to use the downhole petrophysical data
        such as gamma ray, propagation resistivity and so on, to update an
        existing pre-well geological model of a section of the earth in such a
        way that the final result depicts the true model picture of the earth
        subsurface.

        This paper focuses on using well CBH-44L to showcase how the use of
        real-time distance-to-boundary (D2B) measurement from a deep reading
        azimuthal propagation resistivity tool is use to correct for depth
        uncertainty in seismic, thereby, improving the chance of successfully
        landing and drilling a horizontal well.
datasets:
  - Sampath1987/offshore_energy
pipeline_tag: sentence-similarity
library_name: sentence-transformers
metrics:
  - cosine_accuracy
model-index:
  - name: SentenceTransformer based on Alibaba-NLP/gte-multilingual-base
    results:
      - task:
          type: triplet
          name: Triplet
        dataset:
          name: ai job validation
          type: ai-job-validation
        metrics:
          - type: cosine_accuracy
            value: 0.7581904530525208
            name: Cosine Accuracy

SentenceTransformer based on Alibaba-NLP/gte-multilingual-base

This is a sentence-transformers model finetuned from Alibaba-NLP/gte-multilingual-base on the offshore_energy dataset. It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.

Model Details

Model Description

Model Type: Sentence Transformer
Base model: Alibaba-NLP/gte-multilingual-base
Maximum Sequence Length: 8192 tokens
Output Dimensionality: 768 dimensions
Similarity Function: Cosine Similarity
Training Dataset:
- offshore_energy

Model Sources

Documentation: Sentence Transformers Documentation
Repository: Sentence Transformers on GitHub
Hugging Face: Sentence Transformers on Hugging Face

Full Model Architecture

SentenceTransformer(
  (0): Transformer({'max_seq_length': 8192, 'do_lower_case': False, 'architecture': 'NewModel'})
  (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
  (2): Normalize()
)

Usage

Direct Usage (Sentence Transformers)

First install the Sentence Transformers library:

pip install -U sentence-transformers

Then you can load this model and run inference.

from sentence_transformers import SentenceTransformer

# Download from the 🤗 Hub
model = SentenceTransformer("Sampath1987/EnergyEmbed-v2")
# Run inference
sentences = [
    'What role did anti-collision analysis play in the drilling of the dual lateral well?',
    'This paper aims to analyze the impact of appraising and developing marginal fields with multiple stacked reservoirs which is quite challenging in terms of techno commercial value. The development of such marginal reservoirs using conventional single horizontal wells drilling and completion is uneconomical. Therefore, it was necessary to engineer a solution that can enhance the commercial value of the project by reducing CAPEX and OPEX. This paper will present the first comprehensive business case, where multiple stacked reservoirs with marginal reserves were studied to produce independently using multilateral completions, granting full accessibility of the laterals while achieving production monitoring and reservoir surveillance.',
    "The most common challenge in horizontal drilling is depth uncertainty which can be due to poor seismic data or interpretation. It is arguable that a successful landing of the wellbore in the reservoir optimally and within the desired zone is the most challenging in most geosteering operation. The presence of fluid contacts such as oil-water-contact (OWC) and gas-oil-contact (GOC) complicates the whole drilling process, most especially if these fluid contacts are not well defined or known. Additionally, the ability to map the boundaries of the reservoir as the BHA drills the lateral section is an added advantage to remaining within the desired reservoir section.\nThe success of any reservoir navigation service where seismic uncertainty at the reservoir top is high will rely largely on how effective the geosteering system is and how the geosteering engineer is able to react promptly to changes while landing the well in the reservoir and drilling the lateral section with without exiting the reservoir.\nReservoir Navigation Service (RNS) provides the means for the drilling near horizontal or horizontal wells for the purpose of increasing hydrocarbon extraction from the earth's subsurface. This involves the use of a pre-defined bottom hole assembly (BHA) with inbuilt downhole logging while drilling (LWD) and measurement while drilling (MWD) sensors. The measurements from these downhole sensors are uplinked to the surface of the wellbore where they are converted to meaningful petrophysical data. The goal is to use the downhole petrophysical data such as gamma ray, propagation resistivity and so on, to update an existing pre-well geological model of a section of the earth in such a way that the final result depicts the true model picture of the earth subsurface.\nThis paper focuses on using well CBH-44L to showcase how the use of real-time distance-to-boundary (D2B) measurement from a deep reading azimuthal propagation resistivity tool is use to correct for depth uncertainty in seismic, thereby, improving the chance of successfully landing and drilling a horizontal well.",
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 768]

# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)
print(similarities)
# tensor([[1.0000, 0.5285, 0.4524],
#         [0.5285, 1.0000, 0.5421],
#         [0.4524, 0.5421, 1.0000]])

Evaluation

Metrics

Triplet

Dataset: ai-job-validation
Evaluated with TripletEvaluator

Metric	Value
cosine_accuracy	0.7582

Training Details

Training Dataset

offshore_energy

Dataset: offshore_energy at 0ebbfc6
Size: 89,129 training samples
Columns: anchor, positive, and negative

Approximate statistics based on the first 1000 samples:

	anchor	positive	negative
type	string	string	string
details	min: 12 tokens mean: 24.68 tokens max: 77 tokens	min: 37 tokens mean: 437.61 tokens max: 983 tokens	min: 28 tokens mean: 410.96 tokens max: 1188 tokens

Samples:

anchor	positive	negative
`What is the significance of end point relative permeability of the oil phase in the productivity of oil reservoirs below bubble point pressure?`	In contrast with what is followed for Offshore Oil Operations the majority of the Onshore Oil Operations in the world do not have a Minimum and Mandatory required HSE training program for all personnel including contractors and subcontractors. A comparison is drawn between the Minimum and Mandatory HSE Training Programmes applied offshore in developed areas, mainly North Sea and Gulf of Mexico and the benefits that similar programs can bring to the ME onshore oil operations are addressed by estimating the risk reduction and potential economic benefits. The applicability of such Minimum and Mandatory HSE Training Programs is analyzed against the scenario of heavy utilization of contractors and subcontractors with different approach and standards in HSE training and also the increasing complexity of the onshore oil operations An estimation of how many lives can potentially be saved by the introduction of such programs is provided in global and generic terms. The HR Impact, in different a...	The knowledge of relative permeability is key in oil production mechanism as it affects multiphase flow which is vital to producible reserves in petroleum reservoirs. In this study, the impact of altering end point saturation on relative permeability curve and how it influences oil recovery was investigated on field X in Niger Delta, Nigeria. The saturation end points obtained after a simulation study was used as a start point to predict oil production. These end points saturation of water and oil were altered and varied according to facies. The eclipse simulation tool was used in conducting the prediction runs. The result obtained showed wide variation from actual production forecast (i.e. ≥ 25%) when end points were varied with no guided limit from experimental data. This study reveals the need for an accurate determination of residual oil saturation as it was seen to have an impact on forecast and history match.
`What role does the effective coefficient of discharge (Kd) play in calculating the required effective discharge area?`	96 API S TANDARD 520, P ART I—S IZING AND S ELECTION B.2.3.3 Using the theoretical mass flux obtained from numerical integration above, one may determine the required effective discharge area: In USC units: Q × ρ 1 × sec gal G × 60 × 7 4805 . min ft 3 A = W = Q × ρ × 1 G × K d 60 sec × 7 4805 . gal G × K d 60 × 7 4805 . d 3 528 62 2 × . 1 2 2 A = × = 0 0148 ft . = 2 135 in. . (B.8) 60 7 4805 × . 7 592 14 0 65, . × . In SI units: Q ×ρ 1 × sec liter G × 60 min × 1 000, m 3 A = W = Q ×ρ × 1 G × K d 60 sec × 1 000, liter 3 G × K , A = 2 000, × 996 9 . × 1 = 1 379 . × 10 − 3 m 2 = 1 379 mm, 2 (B.9) 60 × 1 000, 37 068, × 0 65 . where G is the theoretical mass flux through the nozzle, lb/s·ft [2] (kg/s·m [2] ); W is the required relief rate, lb/s (kg/s); Q is the required relief rate, gal/min (L/min); ρ = 1 v is the fluid density, lb/ft [3] (kg/m [3] ); K d is the effective coefficient of discharge...	S IZING, S ELECTION, AND I NSTALLATION OF P RESSURE - RELIEVING D EVICES 59 5.6.3 Sizing for Critical Flow 5.6.3.1 General 5.6.3.1.1 Pressure-relief devices in gas or vapor service that operate at critical flow conditions (see 5.6.2) may be sized using Equation (2) through Equation (7). Each of the equations may be used to calculate the effective discharge area, A, required to achieve a required flow rate through a pressure-relief device. A PRV that has an effective discharge area equal to or greater than the calculated value of A is then chosen for the application. In USC units: A = (2) A = (3) 6 32 . CK P K K d 1 b c A = (4) 1 175 . CK P K K 1 175 . CK P K K d 1 b c . In SI units: A = (5) A = (6) CK P K K d 1 b c A = CK P K K = (7) d 1 b c where A is the required effective discharge area of the device, in. [2] (mm [2] ) (see 3.20); W is the required flow through the device, lb/h (kg/h); _C...
`How many swellable packers were required to be run in the horizontal hole part for the AICV trial, and what was the purpose of this requirement?`	Removing fluid from a wellbore column, allowing a well to flow initially, or bringing a previous well back online, nitrogen lifting is commonly used in north Iraq wells. Due to the inability of coiled tubing units to be delivered on time and their high cost, operators are forced to seek for an alternative method of unloading drilling fluid. A hydraulic Jet Pump is a technology used to complete the task. A newly drilled well DB-H was chosen, and the drilling fluid volume calculated was 12,000 bbl. to pump to the surface and begin production, assuming nonstop operation between unloading and producing. The deployment of the hydraulic lift Jet Pump for both stages was planned. Well data from the operator was collected, the process design was initiated, and Jet Evaluation Modeling Software (JEMS) was used to run the design models. A Proper pump size was set up based on available data to meet operator expectations. A Reverse Circulating Jet Pump (RCJP) was chosen to be installed inside a Sli...	This development, predominantly from four artificial islands, of a giant offshore field in the United Arab Emirates (UAE) requires lateral compartmentalization with open hole packers of the 6 5/8" horizontal lower completions with lateral lengths greater than 16,000ft and total well lengths greater than 30,000ft MD. Swell Packer technology has enabled cost effective compartmentalization in horizontal laterals and is the preferred OH packer solution for the development. Deploying swell packers is regarded as being a simple solution to compartmentalizing any lateral where typically the deployment fluid differs from the fluids in which it will swell in; this application prevents the elastomer from swelling during deployment and swelling upon contact with produced or injected fluids. The use of an extended delayed oil swell packer with no delay systems in this particular application enables the packers to be deployed in a Non Aqueous Reservoir Drill in Fluid (RDFNAF) where the packer is re...

Loss: MultipleNegativesRankingLoss with these parameters:

{
    "scale": 20.0,
    "similarity_fct": "cos_sim",
    "gather_across_devices": false
}

Evaluation Dataset

offshore_energy

Dataset: offshore_energy at 0ebbfc6
Size: 11,141 evaluation samples
Columns: anchor, positive, and negative

Approximate statistics based on the first 1000 samples:

	anchor	positive	negative
type	string	string	string
details	min: 12 tokens mean: 24.37 tokens max: 53 tokens	min: 38 tokens mean: 428.35 tokens max: 978 tokens	min: 29 tokens mean: 405.3 tokens max: 1111 tokens

Samples:

anchor	positive	negative
`How does partial jacket construction differ for vessels that cannot use staybolt construction?`	9-7 – 9-10 ASME BPVC.VIII.1-2019 Figure 9-7 (2) Partial jackets that by virtue of their service or configuration do not lend themselves to staybolt construction may be fabricated by other means providing they are designed using appropriate stress values and are proof tested in accordance with UG-101(p). 444 9-8 FABRICATION (a) Fabrication of vessels shall be in accordance with applicable Parts of Subsection A and Subsection B, Part UW. The requirements of UW-13(e) do not apply to closure rings. (b) This Appendix covers fabrication of jacketed vessels by welding. Other methods of fabrication are permitted, provided the requirements of applicable parts of this Di vision are met. (c) Where only the inner vessel is subjected to lethal service, the requirements of UW-2 shall apply only to welds in the inner vessel and those welds attaching the jacket to the inner vessel. Welds attaching the jacket to the inner vessel need not be radiographed and may b...	9-5 – 9-7 ASME BPVC.VIII.1-2019 ‐ ‐ (g 5), and (g 6), may be used on any of the types of jacketed vessels shown in Figure 9-2 where t rj does not exceed [5] / 8 in. (16 mm). (7) Closures shown in Figure 9-5, sketch (h) used on Type 3 jacketed vessels shown in Figure 9-2 shall have attachment welds in accordance with Figure 9-5, sketch ‐ ‐ (i 1) or (i 2). This construction is limited to jackets where t rj does not exceed [5] / 8 in. (16 mm). (8) Closures for conical or toriconical jackets shown in Figure 9-5, sketches (k) and (l) shall comply with the requirements for Type 2 jacketed vessels shown in Figure 9-2. (d) Any radial welds in closure members shall be buttwelded joints penetrating through the full thickness of the member and shall be ground flush where attachment welds are to be made. (e) Where the inner vessel must meet the requirements of UW-2, the attachment welds of the jacket to the inner vessel need not be welded for their full thickness no...
`What dimensions must fins and studs conform to as stipulated in Section 17.4.4?`	17.4 Examination of other components 17.4.1 Examination of heater steelwork shall be in accordance with the structural design code. 17.4.2 Refractory linings shall be examined throughout for thickness variations during application and for cracks after curing. Thickness tolerance is limited to a range of minus 6 mm (1/4 in) to plus 13 mm (1/2 in). Cracks which are 3 mm (1/8 in) or greater in width and penetrate more than 50 % of the castable thickness shall be repaired. Repairs shall be made by chipping out the unsound refractory to the backup layer interface or casing and exposing a minimum of three tieback anchors, or to the sound metal, making a joint between sound refractory that has a minimum slope of 25 mm (1 in) to the base metal (dove-tail construction) and then gunning, casting or hand-packing the area to be repaired. 17.4.3 Finned extended surface shall be examined to ensure fins are perpendicular to the tube within 15°. The maximum discontinuity of the w...	16.1 -112 STEEL ANCHORS [Sect. I8. 3e. Detailing Requirements in Composite Components Steel anchors in composite components shall meet the following requirements: (a) Minimum concrete cover to steel anchors shall be in accordance with ACI 318 provisions for concrete protection of headed shear stud reinforcement. (b) Minimum center-to-center spacing of steel headed stud anchors shall be four diameters in any direction. (c) The maximum center-to-center spacing of steel headed stud anchors shall not exceed 32 times the shank diameter. (d) The maximum center-to-center spacing of steel channel anchors shall be 24 in. (600 mm). User Note: Detailing requirements provided in this section are absolute limits. See Sections I8.3a, I8.3b and I8.3c for additional limitations required to preclude edge and group effect considerations. Specification for Structural Steel Buildings, July 7, 2016 A MERICAN I NSTITUTE OF S TEEL C ONSTRUCTION
`What are some common mistakes in oil and gas project execution that lead to financial losses?`	Dozens of deepwater wells have been drilled in western South China Sea with about 30 percent have characteristics of high temperature and high pressure, which brought a series of difficulties and challenges to field operations. After incorporating the analysis of engineering and geological environment for deepwater HTHP wells in Lingshui block of western South China Sea, it is suggested that the solution of drilling problems for deepwater HTHP wells should start from drilling fluid. Several major technical problems are required to be addressed by drilling fluid, such as co-exist of low temperature and high temperature that lead to difficulty of drilling fluid maintenance and narrow density margin caused by deepwater and high pressure. Based on the above problems, combining with geological features of HTHP wells, researchers developed a novel water based drilling fluid system compatible with deepwater HTHP wells in Lingshui block on the basis of conventional HEM drilling fluid and furth...	The lack of availability of required skills and experience in most if not all parts of the oil and gas value chain is well documented so, rather than trying to make the case, we will summarise the challenge thus: the industry in all parts of the world can't find the capability it needs to safely get its work done in the timeframes it would like. However or wherever the situation is measured, the consequence is that in days when the oil price might suggest that the industry has "never had it so good", many companies are falling seriously short of stakeholder expectations with projects of all types not being completed as planned or failing to deliver anticipated returns. Close to home we see producers consistently missing quarterly production targets and a seemingly constant downgrading of forecasts and year-on-year plans. This leads to a constant stream of bad news and criticism in the media, greater stress through all levels of management and an inevitable "knee jerk" towards a more sh...

Loss: MultipleNegativesRankingLoss with these parameters:

{
    "scale": 20.0,
    "similarity_fct": "cos_sim",
    "gather_across_devices": false
}

Training Hyperparameters

Non-Default Hyperparameters

eval_strategy: steps
per_device_train_batch_size: 16
per_device_eval_batch_size: 16
learning_rate: 2e-05
num_train_epochs: 2
warmup_ratio: 0.1

All Hyperparameters

Click to expand

overwrite_output_dir: False
do_predict: False
eval_strategy: steps
prediction_loss_only: True
per_device_train_batch_size: 16
per_device_eval_batch_size: 16
per_gpu_train_batch_size: None
per_gpu_eval_batch_size: None
gradient_accumulation_steps: 1
eval_accumulation_steps: None
torch_empty_cache_steps: None
learning_rate: 2e-05
weight_decay: 0.0
adam_beta1: 0.9
adam_beta2: 0.999
adam_epsilon: 1e-08
max_grad_norm: 1.0
num_train_epochs: 2
max_steps: -1
lr_scheduler_type: linear
lr_scheduler_kwargs: {}
warmup_ratio: 0.1
warmup_steps: 0
log_level: passive
log_level_replica: warning
log_on_each_node: True
logging_nan_inf_filter: True
save_safetensors: True
save_on_each_node: False
save_only_model: False
restore_callback_states_from_checkpoint: False
no_cuda: False
use_cpu: False
use_mps_device: False
seed: 42
data_seed: None
jit_mode_eval: False
use_ipex: False
bf16: False
fp16: False
fp16_opt_level: O1
half_precision_backend: auto
bf16_full_eval: False
fp16_full_eval: False
tf32: None
local_rank: 0
ddp_backend: None
tpu_num_cores: None
tpu_metrics_debug: False
debug: []
dataloader_drop_last: False
dataloader_num_workers: 0
dataloader_prefetch_factor: None
past_index: -1
disable_tqdm: False
remove_unused_columns: True
label_names: None
load_best_model_at_end: False
ignore_data_skip: False
fsdp: []
fsdp_min_num_params: 0
fsdp_config: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
fsdp_transformer_layer_cls_to_wrap: None
accelerator_config: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
deepspeed: None
label_smoothing_factor: 0.0
optim: adamw_torch
optim_args: None
adafactor: False
group_by_length: False
length_column_name: length
ddp_find_unused_parameters: None
ddp_bucket_cap_mb: None
ddp_broadcast_buffers: False
dataloader_pin_memory: True
dataloader_persistent_workers: False
skip_memory_metrics: True
use_legacy_prediction_loop: False
push_to_hub: False
resume_from_checkpoint: None
hub_model_id: None
hub_strategy: every_save
hub_private_repo: None
hub_always_push: False
hub_revision: None
gradient_checkpointing: False
gradient_checkpointing_kwargs: None
include_inputs_for_metrics: False
include_for_metrics: []
eval_do_concat_batches: True
fp16_backend: auto
push_to_hub_model_id: None
push_to_hub_organization: None
mp_parameters:
auto_find_batch_size: False
full_determinism: False
torchdynamo: None
ray_scope: last
ddp_timeout: 1800
torch_compile: False
torch_compile_backend: None
torch_compile_mode: None
include_tokens_per_second: False
include_num_input_tokens_seen: False
neftune_noise_alpha: None
optim_target_modules: None
batch_eval_metrics: False
eval_on_start: False
use_liger_kernel: False
liger_kernel_config: None
eval_use_gather_object: False
average_tokens_across_devices: False
prompts: None
batch_sampler: batch_sampler
multi_dataset_batch_sampler: proportional
router_mapping: {}
learning_rate_mapping: {}

Training Logs

Epoch	Step	Training Loss	Validation Loss	ai-job-validation_cosine_accuracy
0.1795	1000	-	1.1499	0.6699
0.3590	2000	-	1.0897	0.6842
0.5385	3000	-	1.0492	0.7062
0.7180	4000	-	1.0260	0.7209
0.8975	5000	1.1918	1.0042	0.7281
1.0770	6000	-	1.0018	0.7334
1.2565	7000	-	0.9779	0.7456
1.4360	8000	-	0.9708	0.7486
1.6155	9000	-	0.9583	0.7560
1.7950	10000	0.9342	0.9509	0.7606
1.9745	11000	-	0.9479	0.7582

Framework Versions

Python: 3.10.12
Sentence Transformers: 5.1.0
Transformers: 4.53.3
PyTorch: 2.8.0+cu128
Accelerate: 1.9.0
Datasets: 4.0.0
Tokenizers: 0.21.2

Citation

BibTeX

Sentence Transformers

@inproceedings{reimers-2019-sentence-bert,
    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2019",
    publisher = "Association for Computational Linguistics",
    url = "https://arxiv.org/abs/1908.10084",
}

MultipleNegativesRankingLoss

@misc{henderson2017efficient,
    title={Efficient Natural Language Response Suggestion for Smart Reply},
    author={Matthew Henderson and Rami Al-Rfou and Brian Strope and Yun-hsuan Sung and Laszlo Lukacs and Ruiqi Guo and Sanjiv Kumar and Balint Miklos and Ray Kurzweil},
    year={2017},
    eprint={1705.00652},
    archivePrefix={arXiv},
    primaryClass={cs.CL}
}