AI/machine learning

Fuzzy Logic Assesses Interwell Connectivity: Case Study of a Giant Presalt Reservoir

This work applies fuzzy logic, a well-established artificial-intelligence technique, to quantitatively assess connectivity between injectors and producers in a giant presalt field in the Santos Basin of Brazil.

Fig. 1—3D graph of the LET for the I4 injector well (upper range).
Fig. 1—3D graph of the LET for the I4 injector well (upper range).
Source: SPE 231704.

Carbonate reservoir characterization is challenged by strong heterogeneities and diagenetic features such as fractures and karsts, which affect well-connectivity knowledge critical for drainage and recovery planning. The complete paper applies fuzzy logic, a well-established artificial-intelligence technique, to assess connectivity between injectors and producers quantitatively in a giant presalt field in the Santos Basin of Brazil. Using field data, the fuzzy system fuses qualitative expert insights into a quantitative connectivity index. The results support local model adjustments and fieldwide injection strategies, improving reservoir management.

×
SPE_logo_CMYK_trans_sm.png
Continue Reading with SPE Membership
SPE Members: Please sign in at the top of the page for access to this member-exclusive content. If you are not a member and you find JPT content valuable, we encourage you to become a part of the SPE member community to gain full access.