Pipeline de OCR para Documentos de Campo
Turns decades of scanned reports, logs and maps into searchable text, including Persian and Arabic documents and handwritten annotations.
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83 de 83 capacidades
Turns decades of scanned reports, logs and maps into searchable text, including Persian and Arabic documents and handwritten annotations.
Pulls the numbers out of the reports — depths, rates, pressures, volumes, dates — and puts them into a database with a link back to the page they came from.
Works out what each document is and which well, field and date it belongs to, so the archive becomes navigable rather than a folder tree.
Establishes one authoritative record per well that every other system agrees with, including a single answer to how deep it is and where the top of the reservoir sits.
Adopts the industry data standard so that your data is portable between vendors, without requiring the full OSDU platform on your own infrastructure.
Gets the live sensor data out of the control system safely and stores it at full resolution, which almost nothing else on this site does.
Continuously checks incoming data for stuck sensors, impossible values, missing periods and broken units, and reports the field’s data health as a number.
Answers "where did this number come from" for any figure in any report, and lists what exists and who owns it.
A paid four-to-six week study that tells you, before you commit to anything, which capabilities your data can actually support today.
Rate of penetration is how fast the bit makes hole. This recommends the weight and rotation speed that make it fastest without wrecking the bit.
A kick is formation fluid entering the wellbore. Left unchecked it becomes a blowout. This watches eleven sensor streams and warns the crew minutes earlier than pit-volume alarms do.
Mud that disappears into the formation is telling you something about how easily fluid moves through the rock. This reads that signal instead of discarding it.
Predicts the mud weight window that keeps the hole open — not too light and it caves, not too heavy and it fractures.
Warns that the string is becoming hard to move, typically twenty to sixty minutes before it stops moving at all.
Compares what the string should weigh and how hard the pumps should work against what is actually measured, and flags the gap.
Recommends the mud formulation for the next section based on what worked in comparable sections, and what it cost.
Predicts whether the cement behind the casing will isolate properly, from the job data, before the evaluation log is run.
Keeps the horizontal well inside the target layer by continuously re-matching the measured logs to the geological model.
Estimates how much drilling the bit has left, so the trip happens on purpose rather than after a failure.
Drafts the casing, mud and BHA programme for a new well from the field’s own drilling history, for an engineer to review.
Watches the mud pumps, top drive and drawworks for the vibration and temperature patterns that precede a breakdown.
Reads every daily drilling report the operator has ever filed and answers, in seconds, what went wrong at this depth in this field before.
Checks the planned and actual well path against every other well on the pad, with the survey uncertainty included.
Helps hold bottom-hole pressure inside a narrow window by predicting what the choke needs to do before the transient arrives.
Listens to pumps, compressors and turbines continuously and identifies the specific defect — bearing, imbalance, misalignment, looseness — from the vibration signature.
Puts every piece of equipment into one reliability taxonomy so that failure rates mean the same thing across all fields, and maintenance is planned from them.
Tunes separator and desalter operation to meet the export specification with less chemical, less heat and fewer off-spec events.
Predicts where a line is corroding fastest and how long it has left, so inspection and replacement go where the risk actually is.
Allocates a fixed inspection budget to the equipment where failure would hurt most and is most likely, with the reasoning written down.
Tracks every well’s barriers and annulus pressures against the operating envelope, and escalates the wells that are outside it.
Shows where the field’s fuel and power actually go, per barrel, and which equipment is drifting away from its best efficiency.
A live process model of the plant that stays calibrated against the real one, used to test a change before making it.
Uses the cameras already installed to spot missing protective equipment, people in restricted zones and unsafe proximity to lifting operations.
Adds optical gas imaging and flame detection on camera to the fixed point detectors, so a leak between detectors is still seen.
Builds a methane inventory from measurements rather than from emission factors, at the level of detail OGMP 2.0 actually asks for.
Watches the flare on camera to confirm it is lit, estimate how much is being burned, and detect smoking or incomplete combustion.
A technician photographs a nameplate and the equipment record is created or matched, instead of being typed from memory later.
Knows who is on site and roughly where, so a muster after an alarm takes minutes instead of a headcount by radio.
Flies or drives the inspection route so that people do not have to work at height or enter confined spaces as often.
Watches the control network passively for devices, traffic and commands that should not be there.
Ask a question about your own field in Persian, Arabic, English or Spanish and get an answer with the report and page it came from.
A model further trained on petroleum engineering text, so it uses the field’s vocabulary correctly in Persian and Arabic as well as English.
Understands log images, maps and cross-sections alongside text, so you can ask a question about a figure rather than only about a paragraph.
Answers questions that need live data by querying the systems directly — "which wells are down and for how long" — and shows the query it ran.
Produces the daily, weekly and monthly reports from the data automatically, with the narrative drafted and the numbers already reconciled.
Captures what the experienced engineers know before they retire, in a form the next engineer can actually find.
Operators record readings and observations on a phone that works with no signal, and everything syncs when the device gets back to coverage.
Moves permits and isolation certificates off paper, so conflicting work on the same equipment is blocked automatically rather than caught by memory.
Connects the platform’s predictions to the systems that actually create work orders and order parts, so an alert becomes a scheduled job.
Tracks what tubulars and critical spares actually exist, where they are, and what the drilling programme will need them for.
Plans crew, vehicle and material movements across the field so that fewer kilometres are driven, which is also the largest safety exposure most operators have.
Lets operators practise upsets and start-ups against a model of their own plant, and records what they can demonstrably do.
One room, and one screen layout, where production, drilling, maintenance and HSE see the same numbers at the same time.
Brings the recommendations from every capability into one prioritised queue, so the team works the highest-value item rather than the loudest alarm.
Forecasts what each well will produce next month, and tells you which wells it is not confident about.
When a well drops, it names the likely cause — scale, water breakthrough, lift failure, choke or reservoir — instead of only flagging the drop.
Decides how to split a limited supply of lift gas across the wells that want it, to maximise oil rather than gas injected.
Watches the downhole pump’s electrical and pressure signature to warn of gas lock, wear or burnout before the well stops.
Reads the dynamometer card automatically and names the downhole condition — gas interference, fluid pound, worn valve, parted rod.
Estimates each well’s oil, water and gas rate continuously from pressure and temperature, between the physical tests.
Splits the metered facility total back to individual wells with a documented, repeatable method instead of a spreadsheet nobody can audit.
Predicts where wax, hydrate, scale or slugging will form in the flowline before the line blocks.
Chooses which wells will actually respond to an acid job, and what volume and placement to use.
Decides which wells will produce sand and sizes the gravel and screen for the ones that will.
Works out which injector is actually supporting which producer, and where the injected water is being wasted.
Ranks which wells to intervene on next by expected barrels per dollar, with rig availability in the calculation.
Runs the inflow-outflow calculation for every well in the field on a schedule, instead of for a few wells when someone has time.
Optimises the whole surface network together — chokes, routing and separator pressures — rather than one well at a time.
A learned stand-in for the full reservoir simulator that answers in seconds instead of hours, so an engineer can test fifty scenarios instead of three.
Tunes the reservoir model until it reproduces what the field actually produced, automatically and with the uncertainty kept rather than discarded.
Labels rock type from well logs across hundreds of wells consistently, which a team of interpreters working separately cannot do.
Measures porosity, grain size and fracture density from core photographs and CT scans instead of from a description written twenty years ago.
Fills the rock between wells with geologically plausible detail instead of a smooth interpolation that no outcrop ever looked like.
Picks faults and horizons across a full seismic volume in hours, leaving the interpreter to judge rather than to click.
Finds the bad intervals in the log archive and reconstructs curves that were never run, so the field has a complete set to work from.
Searches injection strategies — what to inject, where, and at what rate — against recovery and cost together.
Rules out the EOR methods that cannot work in this reservoir before anyone spends a year simulating them.
Searches for where the next wells should go, with drilling feasibility and surface constraints inside the search rather than applied afterwards.
Produces P10, P50 and P90 production forecasts whose spread is calculated, not chosen to look reasonable.
Reads pressure build-up data, proposes the reservoir model behind it, and flags the tests that are not interpretable.
Extracts fluid study data from decades of laboratory reports and tunes the equation of state against all of it, not against the one report someone had to hand.
Fits decline curves across every well in the field on a consistent basis and keeps the audit trail that a reserves report needs.
Evaluates whole development concepts — well count, phasing, facility size — as one connected problem instead of four separate studies.