Announcement • Jul 29
Visionwave Holdings Files U.S. Non-Provisional Patent Application for DeepWave Rf Technology
VisionWave Holdings, Inc. filed a U.S. non-provisional utility patent application relating to its DeepWave RF technology, an advanced subsurface sensing and visualization platform designed for drilling, geological exploration, and related industrial applications. The application, U.S. Patent Application No. 19/752,680, is titled 'Systems and Methods of Integrated Software-Defined Radio and Drilling for Near-Bit Subsurface Sensing and Visualization.' The application was filed with the United States Patent and Trademark Office on July 24, 2026, and identifies Dr. Danny Rittman as the first named inventor. The filing is a non-provisional application claiming priority to U.S. Provisional Patent Application No. 64/032,626, filed April 8, 2026 (titled as - NEAR-BIT SUBSURFACE RF SENSING SYSTEMS). No assurance can be given that a patent will be issued from either application or, if a patent is issued, as to the scope of any claims that may ultimately be allowed. DeepWave RF is being developed to address one of the drilling industry’s most persistent challenges: the limited ability to understand geological formations before the drill bit physically reaches them. Conventional logging-while-drilling systems primarily measure conditions surrounding the drilling assembly. DeepWave RF is designed to shift that model toward anticipatory sensing by examining the formation directly ahead of and around the drill bit. The proposed architecture integrates a software-defined radio platform with the drill string or bottom-hole assembly, together with a near-bit antenna system, adaptive RF waveform control, edge processing, and an AI-assisted hybrid inversion engine. The system is designed to process received electromagnetic signals and convert them into a probabilistic representation of the subsurface formation. Rather than transmitting large volumes of raw downhole data to the surface, DeepWave RF is intended to perform critical processing close to the point of measurement. Its AI architecture may use physics-informed neural networks, or PINNs, that incorporate Maxwell’s equations into the learning and inversion process. This approach is designed to accelerate subsurface interpretation while helping ensure that AI-generated results remain consistent with known electromagnetic physics. The platform is intended to identify and characterize subsurface features such as fractures and fracture corridors, geological and lithological boundaries, voids and cavities, gas-related anomalies, fluid contacts and water-bearing zones, changes in rock properties, and mineralized or metal-bearing structures. DeepWave RF may provide operators with information such as the estimated range and direction of an anomaly, its probable classification, and an associated confidence level. The resulting information may be presented as a dynamic two-dimensional or three-dimensional look-ahead visualization, a 360-degree subsurface view, a hazard alert, or a confidence-ranked geological map. The system is designed to adapt its RF sensing parameters to changing geological and drilling conditions. In favorable resistive formations, the architecture described in the application is designed to achieve look-ahead sensing distances in the tens-of-meters range with improved structural detail. Actual range and resolution would depend on formation conductivity, dielectric properties, drilling fluid, antenna configuration, and other operating conditions. The patent application expressly recognizes that highly conductive formations may substantially reduce achievable RF penetration. Potential benefits of the DeepWave RF platform, if the technology is successfully developed and commercialized, could include improved geosteering, earlier detection of drilling hazards, reduced risk of unexpected formation changes, improved reservoir-zone navigation, and better-informed decisions during drilling operations. The technology could also help operators distinguish between broad geological boundaries and discrete structures such as fractures, voids, or localized gas pockets. Although oil and gas drilling represents an important potential application, the technology is designed for a broader range of subsurface industries, including geothermal energy, mineral exploration, water detection, salt navigation, deepwater drilling, geological surveying, archaeological exploration, and paleontological investigation. The filing represents another step in VisionWave’s strategy of combining artificial intelligence, radio-frequency sensing, edge computing, and advanced visualization to address complex industrial and infrastructure challenges.
