In a forensic-voice-comparison (FVC) case, one speaker (A) was talking on a mobile telephone, and another (B) was standing a short distance away. Later, B moved closer to the telephone. Shortly thereafter, there was a section of speech where the identity of the speaker was disputed. All material for training an FVC-system could be extracted from this single recording, but there was a near-far mismatch: Training data for A were near, training data for B were far, and the disputed speech was near. We describe a procedure for addressing the degree of validity and reliability of an FVC system under such conditions, prior to it being applied to the casework recording: Sections of recordings of pairs of speakers of known identity are used to train an A and a B model; multiple other sections from each of the A and B recordings are used as test data; a likelihood ratio is calculated for each test section; and system validity and reliability are assessed. Prior to training and testing, the A and B recordings were played through loudspeakers and rerecorded via a mobile-telephone network, B was rerecorded twice, once with the loudspeaker near and once with it far from the telephone.