公开(公告)号：US12067505B2

公开(公告)日：2024-08-20

申请号：US18306640

申请日：2023-04-25

Applicant: FREEPORT MINERALS CORPORATION

Inventor： Dana Geislinger ,  Travis Gaddie ,  Margaret Alden Tinsley ,  Muneeb Alam ,  Steven Chad Richardson ,  Akaash Sanyal ,  Raquel Crossman ,  Tianfang Ni ,  Cory A. Demieville ,  Luke Gerdes ,  Robyn Freeman ,  Oleksandr Klesov ,  Luciano Kiniti Issoe

IPC: G06Q10/04 ,  C22B3/06 ,  C22B15/00 ,  G06Q10/0631 ,  G06Q50/02

CPC classification number: G06Q10/04 ,  C22B3/06 ,  C22B15/0067 ,  C22B15/0095 ,  G06Q10/0631 ,  G06Q50/02

Abstract: The method may comprise receiving historical data (e.g., mineralogy data, irrigation data, raffinate data, heat data, lift height data, geographic data on ore placement and/or blower data); training a predictive model using the historical data to create a trained predictive model; adding future assumption data to the trained predictive model; running the forecast engine for a plurality of parameters to obtain forecast data for a mining production target; comparing the forecast data for the mining production target to the actual data for the mining production target; determining deviations between the forecast data and the actual data, based on the comparing; and changing each of the plurality of parameters from the forecast data to the actual data to determine a contribution to the deviations for each of the plurality of parameters.

公开(公告)号：US11948103B2

公开(公告)日：2024-04-02

申请号：US18339998

申请日：2023-06-22

Applicant: FREEPORT MINERALS CORPORATION

Inventor： Dana Geislinger ,  Travis Gaddie ,  Margaret Alden Tinsley ,  Muneeb Alam ,  Steven Chad Richardson ,  Akaash Sanyal ,  Raquel Crossman ,  Tianfang Ni ,  Cory A. Demieville ,  Luke Gerdes ,  Robyn Freeman ,  Oleksandr Klesov ,  Luciano Kiniti Issoe

IPC: G06Q10/04 ,  C22B3/06 ,  C22B15/00 ,  G06Q10/0631 ,  G06Q50/02

CPC classification number: G06Q10/04 ,  C22B3/06 ,  C22B15/0067 ,  C22B15/0095 ,  G06Q10/0631 ,  G06Q50/02

Abstract: The method may comprise receiving historical data (e.g., mineralogy data, irrigation data, raffinate data, heat data, lift height data, geographic data on ore placement and/or blower data); training a predictive model using the historical data to create a trained predictive model; adding future assumption data to the trained predictive model; running the forecast engine for a plurality of parameters to obtain forecast data for a mining production target; comparing the forecast data for the mining production target to the actual data for the mining production target; determining deviations between the forecast data and the actual data, based on the comparing; and changing each of the plurality of parameters from the forecast data to the actual data to determine a contribution to the deviations for each of the plurality of parameters.

公开(公告)号：US11893519B2

公开(公告)日：2024-02-06

申请号：US18306534

申请日：2023-04-25

Applicant: FREEPORT MINERALS CORPORATION

Inventor： Dana Geislinger ,  Travis Gaddie ,  Margaret Alden Tinsley ,  Muneeb Alam ,  Steven Chad Richardson ,  Akaash Sanyal ,  Raquel Crossman ,  Tianfang Ni ,  Cory A. Demieville ,  Luke Gerdes ,  Robyn Freeman ,  Oleksandr Klesov ,  Luciano Kiniti Issoe

IPC: G06Q10/04 ,  G06Q50/02 ,  C22B15/00 ,  C22B3/06 ,  G06Q10/0631

CPC classification number: G06Q10/04 ,  C22B3/06 ,  C22B15/0067 ,  C22B15/0095 ,  G06Q10/0631 ,  G06Q50/02

Abstract: The method may comprise receiving historical data (e.g., mineralogy data, irrigation data, raffinate data, heat data, lift height data, geographic data on ore placement and/or blower data); training a predictive model using the historical data to create a trained predictive model; adding future assumption data to the trained predictive model; running the forecast engine for a plurality of parameters to obtain forecast data for a mining production target; comparing the forecast data for the mining production target to the actual data for the mining production target; determining deviations between the forecast data and the actual data, based on the comparing; and changing each of the plurality of parameters from the forecast data to the actual data to determine a contribution to the deviations for each of the plurality of parameters.

公开(公告)号：US20230419226A1

公开(公告)日：2023-12-28

申请号：US17850864

申请日：2022-06-27

Applicant: FREEPORT MINERALS CORPORATION

Inventor： Oleksandr Klesov ,  Luke Gerdes ,  Dana Geislinger ,  Margaret Alden Tinsley ,  Robyn Freeman ,  Akaash Sanyal ,  Muneeb Alam ,  Raquel Crossman ,  Travis Gaddie ,  Steven Chad Richardson ,  Tianfang Ni ,  Cory A. Demieville ,  Luciano Kiniti Issoe

IPC: G06Q10/06 ,  G06Q50/02 ,  G01N33/24

CPC classification number: G06Q10/06375 ,  G06Q50/02 ,  G01N33/24

Abstract: The method may comprise receiving historical data (e.g., mineralogy data, irrigation data, raffinate data, heat data, lift height data, geographic data on ore placement and/or blower data); training a predictive model using the historical data to create a trained predictive model; adding future assumption data to the trained predictive model; running the forecast engine for a plurality of parameters to obtain forecast data for a mining production target; comparing the forecast data for the mining production target to the actual data for the mining production target; determining deviations between the forecast data and the actual data, based on the comparing; and changing each of the plurality of parameters from the forecast data to the actual data to determine a contribution to the deviations for each of the plurality of parameters.

公开(公告)号：US20230419198A1

公开(公告)日：2023-12-28

申请号：US18306640

申请日：2023-04-25

Applicant: FREEPORT MINERALS CORPORATION

Inventor： Dana Geislinger ,  Travis Gaddie ,  Margaret Alden Tinsley ,  Muneeb Alam ,  Steven Chad Richardson ,  Akaash Sanyal ,  Raquel Crossman ,  Tianfang Ni ,  Cory A. Demieville ,  Luke Gerdes ,  Robyn Freeman ,  Oleksandr Klesov ,  Luciano Kiniti Issoe

IPC: G06Q10/04 ,  G06Q50/02 ,  G06Q10/0631 ,  C22B15/00 ,  C22B3/06

CPC classification number: G06Q10/04 ,  G06Q50/02 ,  G06Q10/0631 ,  C22B15/0095 ,  C22B3/06 ,  C22B15/0067

Abstract: The method may comprise receiving historical data (e.g., mineralogy data, irrigation data, raffinate data, heat data, lift height data, geographic data on ore placement and/or blower data); training a predictive model using the historical data to create a trained predictive model; adding future assumption data to the trained predictive model; running the forecast engine for a plurality of parameters to obtain forecast data for a mining production target; comparing the forecast data for the mining production target to the actual data for the mining production target; determining deviations between the forecast data and the actual data, based on the comparing; and changing each of the plurality of parameters from the forecast data to the actual data to determine a contribution to the deviations for each of the plurality of parameters.

公开(公告)号：US20230418269A1

公开(公告)日：2023-12-28

申请号：US17850855

申请日：2022-06-27

Applicant: FREEPORT MINERALS CORPORATION

Inventor： Steven Chad Richardson ,  Robyn Freeman ,  Luke Gerdes ,  Margaret Alden Tinsley ,  Dana Geislinger ,  Akaash Sanyal ,  Travis Gaddie ,  Muneeb Alam ,  Raquel Crossman ,  Tianfang Ni ,  Cory A. Demieville ,  Oleksandr Klesov ,  Luciano Kiniti Issoe

IPC: G05B19/418

CPC classification number: G05B19/41865 ,  G05B19/4183 ,  G05B19/41885 ,  C22B3/04

Abstract: The method may comprise receiving historical data (e.g., mineralogy data, irrigation data, raffinate data, heat data, lift height data, geographic data on ore placement and/or blower data); training a predictive model using the historical data to create a trained predictive model; adding future assumption data to the trained predictive model; running the forecast engine for a plurality of parameters to obtain forecast data for a mining production target; comparing the forecast data for the mining production target to the actual data for the mining production target; determining deviations between the forecast data and the actual data, based on the comparing; and changing each of the plurality of parameters from the forecast data to the actual data to determine a contribution to the deviations for each of the plurality of parameters.

公开(公告)号：US20230417570A1

公开(公告)日：2023-12-28

申请号：US17850880

申请日：2022-06-27

Applicant: FREEPORT MINERALS CORPORATION

Inventor： Dana Geislinger ,  Margaret Alden Tinsley ,  Akaash Sanyal ,  Robyn Freeman ,  Travis Gaddie ,  Muneeb Alam ,  Steven Chad Richardson ,  Raquel Crossman ,  Tianfang Ni ,  Cory A. Demieville ,  Luke Gerdes ,  Oleksandr Klesov ,  Luciano Kiniti Issoe

IPC: G01C21/00

CPC classification number: G01C21/3811 ,  G01C21/3826

Abstract: The method may comprise receiving historical data (e.g., mineralogy data, irrigation data, raffinate data, heat data, lift height data, geographic data on ore placement and/or blower data); training a predictive model using the historical data to create a trained predictive model; adding future assumption data to the trained predictive model; running the forecast engine for a plurality of parameters to obtain forecast data for a mining production target; comparing the forecast data for the mining production target to the actual data for the mining production target; determining deviations between the forecast data and the actual data, based on the comparing; and changing each of the plurality of parameters from the forecast data to the actual data to determine a contribution to the deviations for each of the plurality of parameters.

公开(公告)号：US20230417552A1

公开(公告)日：2023-12-28

申请号：US17850884

申请日：2022-06-27

Applicant: FREEPORT MINERALS CORPORATION

Inventor： Luciano Kiniti Issoe ,  Tianfang Ni ,  Luke Gerdes ,  Dana Geislinger ,  Travis Gaddie ,  Margaret Alden Tinsley ,  Muneeb Alam ,  Steven Chad Richardson ,  Akaash Sanyal ,  Raquel Crossman ,  Cory A. Demieville ,  Robyn Freeman ,  Oleksandr Klesov

IPC: G01C21/00 ,  G06N5/02

CPC classification number: G01C21/005 ,  G06N5/022 ,  G01C21/3811 ,  G01C21/3826

Abstract: The method may comprise receiving historical data (e.g., mineralogy data, irrigation data, raffinate data, heat data, lift height data, geographic data on ore placement and/or blower data); training a predictive model using the historical data to create a trained predictive model; adding future assumption data to the trained predictive model; running the forecast engine for a plurality of parameters to obtain forecast data for a mining production target; comparing the forecast data for the mining production target to the actual data for the mining production target; determining deviations between the forecast data and the actual data, based on the comparing; and changing each of the plurality of parameters from the forecast data to the actual data to determine a contribution to the deviations for each of the plurality of parameters.

公开(公告)号：US11521138B1

公开(公告)日：2022-12-06

申请号：US17850834

申请日：2022-06-27

Applicant: FREEPORT MINERALS CORPORATION

Inventor： Dana Geislinger ,  Travis Gaddie ,  Margaret Alden Tinsley ,  Muneeb Alam ,  Steven Chad Richardson ,  Akaash Sanyal ,  Raquel Crossman ,  Tianfang Ni ,  Cory A. Demieville ,  Luke Gerdes ,  Robyn Freeman ,  Oleksandr Klesov ,  Luciano Kiniti Issoe

IPC: G06Q10/04 ,  G06Q50/02 ,  C22B15/00 ,  C22B3/06 ,  G06Q10/06

Abstract: The method may comprise receiving historical data (e.g., mineralogy data, irrigation data, raffinate data, heat data, lift height data, geographic data on ore placement and/or blower data); training a predictive model using the historical data to create a trained predictive model; adding future assumption data to the trained predictive model; running the forecast engine for a plurality of parameters to obtain forecast data for a mining production target; comparing the forecast data for the mining production target to the actual data for the mining production target; determining deviations between the forecast data and the actual data, based on the comparing; and changing each of the plurality of parameters from the forecast data to the actual data to determine a contribution to the deviations for each of the plurality of parameters.