METHOD AND SYSTEM FOR THE SEARCH FOR ANALOGUES OF OIL AND GAS FIELDS Russian patent published in 2021 - IPC E21B49/00 G06F16/215 G06N20/20 

Abstract RU 2745492 C1

FIELD: oil and gas.

SUBSTANCE: group of inventions relates to the field of searching for analogs of reservoirs with similar properties and filling in the missing values ​​of descriptive attributes of the reservoir. A computer-implemented method for searching for analogs of deposits includes at least the following steps: get the first and second sample of records from at least one database of deposits and their attributes. Moreover, the first sample of records contains deposits of the first type, described by the first group of attributes, and the second sample of records contains deposits of the second type, described by the second group of attributes. The first sample to be marked out is formed; then a second one; the first and second sample to be marked out are marked with the help of at least two experts. Moreover, for each entry in a subgroup, experts mark whether this entry characterizes a deposit, which is an analogue of the target deposit in this subgroup. The first and second training samples are formed from the first and second labeled samples, respectively. The first classifier is trained using gradient boosting using the transformed attributes of the records of the first training sample; the second classifier is trained using gradient boosting using the transformed attributes of the records of the second training sample. Then the type of field is received from a user as well as the values ​​of its attributes to determine its analogues; transforming the obtained attributes for use by the field classifier and searching for analogues using the trained classifier corresponding to the field type; then the user is presented with information about the search results.

EFFECT: increased efficiency of searching for oil reservoir analogs.

26 cl, 6 dwg

Similar patents RU2745492C1

Title Year Author Number
TRAINING CLASSIFIERS USED TO EXTRACT INFORMATION FROM NATURAL LANGUAGE TEXTS 2018
  • Matskevich Stepan Evgenevich
  • Bulgakov Ilya Aleksandrovich
RU2691855C1
CLASSIFIER TRAINING USED FOR EXTRACTING INFORMATION FROM TEXTS IN NATURAL LANGUAGE 2018
  • Matskevich Stepan Evgenevich
  • Bulgakov Ilya Aleksandrovich
RU2681356C1
SYSTEM AND METHOD FOR TWO-STAGE CLASSIFICATION OF FILES 2018
  • Romanenko Aleksej Mikhajlovich
  • Prokudin Sergej Viktorovich
  • Liskin Aleksandr Viktorovich
RU2708356C1
METHOD FOR CHOOSING THE OPTIMAL HYDRAULIC FRACTURING DESIGN BASED ON THE INTELLIGENT ANALYSIS OF FIELD DATA TO INCREASE THE PRODUCTION OF HYDROCARBON RAW MATERIALS 2021
  • Paderin Grigorij Vladimirovich
  • Shel Egor Vladimirovich
  • Osiptsov Andrej Aleksandrovich
  • Burnaev Evgenij Vladimirovich
  • Vajnshtejn Albert Lvovich
  • Duplyakov Viktor Mikhajlovich
  • Morozov Anton Dmitrievich
  • Popkov Dmitrij Olegovich
RU2775034C1
METHOD OF CALCULATING CLIENT CREDIT RATING 2019
  • Babaev Dmitrij Leonidovich
  • Umerenkov Dmitrij Evgenevich
  • Savchenko Maksim Sergeevich
RU2723448C1
RETRIEVAL OF INFORMATION OBJECTS USING A COMBINATION OF CLASSIFIERS ANALYZING LOCAL AND NON-LOCAL SIGNS 2018
  • Indenbom Evgenij Mikhajlovich
RU2686000C1
METHOD FOR DETERMINING PROBABILITY OF ACTH-ECTOPIC SYNDROME IN PATIENTS WITH ACTH-DEPENDENT ENDOGENOUS HYPERADRENOCORTICISM 2023
  • Golounina Olga Olegovna
  • Belaya Zhanna Evgenevna
  • Voronov Kirill Andreevich
  • Solodovnikov Aleksandr Gennadevich
  • Rozhinskaya Lyudmila Yakovlevna
  • Melnichenko Galina Afanasevna
  • Mokrysheva Natalya Georgievna
  • Dedov Ivan Ivanovich
RU2814146C1
METHOD FOR ATTRIBUTION OF PARTIALLY STRUCTURED TEXTS FOR FORMATION OF NORMATIVE-REFERENCE INFORMATION 2020
  • Fedosin Sergei Alekseevich
  • Plotnikova Natalia Pavlovna
  • Martynov Vladislav Aleksandrovich
  • Ryskin Konstantin Eduardovich
  • Kuznetsov Dmitrii Aleksandrovich
  • Deniskin Aleksandr Vladimirovich
  • Vechkanova Iuliia Sergeevna
  • Fediushkin Nikolai Alekseevich
  • Tsilikov Nikita Sergeevich
RU2750852C1
FUEL COMBUSTION MODES MONITORING SYSTEM BY MEANS OF TORCH IMAGES ANALYSIS USING CLASSIFIER BASED ON CONVOLUTIONAL NEURAL NETWORK 2018
  • Gobyzov Oleg Alekseevich
  • Abdurakipov Sergej Sergeevich
  • Tokarev Mikhail Petrovich
  • Seredkin Aleksandr Valerevich
  • Dulin Vladimir Mikhajlovich
  • Bilskij Artur Valerevich
RU2713850C1
SELECTION OF TEXT CLASSIFIER PARAMETER BASED ON SEMANTIC CHARACTERISTICS 2016
  • Kolotienko Sergej Sergeevich
  • Anisimovich Konstantin Vladimirovich
RU2628431C1

RU 2 745 492 C1

Authors

Slivkin Stanislav Sergeevich

Kharitontseva Polina Anatolevna

Churochkin Ilia Igorevich

Bogoslovskii Nikolai Nikolaevich

Bukhanov Nikita Vladimirovich

Dates

2021-03-25Published

2020-10-09Filed