公开(公告)号：US20240124951A1

公开(公告)日：2024-04-18

申请号：US18398613

申请日：2023-12-28

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：US20230417724A1

公开(公告)日：2023-12-28

申请号：US17850866

申请日：2022-06-27

Applicant: FREEPORT MINERALS CORPORATION

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

IPC: G01N33/24 ,  G01N15/02

CPC classification number: G01N33/24 ,  G01N15/0227

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：US11823099B1

公开(公告)日：2023-11-21

申请号：US18306749

申请日：2023-04-25

Applicant: FREEPORT MINERALS CORPORATION

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

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：US12260371B2

公开(公告)日：2025-03-25

申请号：US17850895

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: G06Q10/0631 ,  G06Q10/0639 ,  G06Q10/087 ,  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：US20250044094A1

公开(公告)日：2025-02-06

申请号：US18925279

申请日：2024-10-24

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 ,  G06N5/022

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：US12169796B2

公开(公告)日：2024-12-17

申请号：US18433776

申请日：2024-02-06

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 ,  G06Q10/06 ,  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：US12259256B2

公开(公告)日：2025-03-25

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

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：US20240418697A1

公开(公告)日：2024-12-19

申请号：US18817158

申请日：2024-08-27

Applicant: FREEPORT MINERALS CORPORATION

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

IPC: G01N33/24 ,  G01N15/0227

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：US12163788B2

公开(公告)日：2024-12-10

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 ,  G06N5/022

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：US12111303B2

公开(公告)日：2024-10-08

申请号：US17850866

申请日：2022-06-27

Applicant: FREEPORT MINERALS CORPORATION

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

IPC: G01N33/24 ,  G01N15/0227

CPC classification number: G01N33/24 ,  G01N15/0227

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.